You'll drive the adoption of safe, frontier AI by securing strategic deals with CPG brands. You'll leverage your consultative sales expertise in the CPG sector to propel revenue growth while becoming a trusted partner to CPG stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities in brand management, supply chain, and category planning.

In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with CPG decision-makers.

The ideal candidate will have a passion for developing new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI.

Responsibilities:

• Win new business and drive revenue for Anthropic within the CPG sector. Navigate complex CPG organisations to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close
• Design and execute innovative sales strategies tailored to CPG procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze CPG market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns
• Spearhead market expansion by identifying new use cases within brand teams, supply chain functions, and commercial operations. Collaborate cross-functionally to differentiate our offerings for CPG applications
• Navigate complex CPG stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus
• Inform product roadmaps and features by gathering feedback from users and conveying CPG market needs. Provide insights that strengthen our value proposition for CPG
• Continuously refine the CPG sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency

Requirements:

• 8+ years of B2B sales experience in SaaS, API solutions, or emerging technologies
• A track record of managing complex sales cycles within CPG organisations and securing strategic deals by understanding both technical requirements and CPG use cases
• Demonstrated ability to navigate CPG organisational structures and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments
• Extensive experience negotiating complex agreements within CPG procurement frameworks and policies
• Proven experience exceeding revenue targets by effectively managing an evolving pipeline and sales process
• Excellent communication skills and the ability to present confidently to various CPG audiences, from brand managers and category leads to senior executives
• Deep understanding of CPG buying cycles, decision-making processes, and key pain points
• A strategic, analytical approach to assessing the CPG market combined with creative, tactical execution to capture opportunities
• A passion for and/or experience with advanced AI systems and their applications. You feel strongly about ensuring frontier AI systems are developed safely and ethically for CPG use

Benefits:

• Annual Salary: £280,000-£330,000 GBP
• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

How to Apply:

If you're interested in this opportunity, please submit your application through our website. We look forward to hearing from you!

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About Anthropic

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole.

About the Role

Security at Anthropic is not a compliance exercise. It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.

Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we'll treat that as useful signals. The questions these projects are designed to answer include:

• Can our core research workflows survive extreme isolation?

• Can we get cryptographic guarantees where we currently rely on trust?

• Can AI become our most effective security control?

As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.

Current Project Areas

The portfolio evolves based on what we learn. Current areas include:

• Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact

• Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production

• Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)

• Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring

• Prototyping API-only access regimes where even internal research workflows never touch raw model weights

Part of your job is helping shape what comes next based on gaps uncovered in the current round.

Responsibilities

• Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results

• Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast

• Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.

• Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break

• Evaluate and integrate emerging security technologies through coordination with external vendors and research groups

• Turn experimental results into clear, decision-ready writeups that inform Anthropic's long-term security architecture and RSP commitments

• Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments

• Help scope and prioritize the next wave of Labs projects based on what the current round uncovers

Requirements

• 7+ years of software or security engineering experience, with a solid foundation in production systems

• Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal

• Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)

• Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly

• A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan

• Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on

• Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward

• Genuine curiosity about what it would actually take to defend against a nation-state-level adversary

• Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well

• Bachelor's degree in Computer Science, a related field, or equivalent industry experience required.

Preferred Qualifications

• Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter

• Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them

• Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives

• Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need

• Background building or operating security systems in environments that demand rapid iteration rather than rigid change control

• Prior work at a startup, on an innovation team, or in an applied research group where shipping a working v0 to answer a real question was explicitly the goal

Location

This role is based in our San Francisco office (500 Howard St). Several Labs projects involve physical secure facilities on-site, so expect to be in-office more frequently than Anthropic's standard 25% hybrid baseline.

What We Offer

• Competitive salary and equity package

• Comprehensive health insurance and retirement plans

• Flexible work arrangements, including remote work options

• Professional development opportunities, including training and conference attendance

• Collaborative and dynamic work environment

• Access to cutting-edge technology and resources

• Opportunity to work on challenging and impactful projects

• Recognition and rewards for outstanding performance

If you're excited about the opportunity to join our team and contribute to the development of secure and beneficial AI systems, please submit your application. We can't wait to hear from you!

Deadline to Apply

None, applications will be received on a rolling basis.

Annual Compensation Range

$405,000 - $485,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with the process.

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For example, you might:

• Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them;
• Design and build harnesses to test AI agents' tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment;
• Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use;
• Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents.

Ideally you'd have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance;
• Practical experience conducting technical research collaboratively;
• Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches;
• A track record of published research in machine learning, particularly in generative AI;
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development;
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect, or similar tools;
• Experience with red-teaming, prompt injection, or adversarial testing of AI systems.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organisational culture. We will not ask any LeetCode-style questions. If you're excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn't perfectly align with every requirement.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

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You will play a critical role in shaping Anthropic's approach to trade compliance as we scale, advising on the development of robust compliance programs that support our mission to develop AI systems that are safe, beneficial, and understandable.

Responsibilities:

• Provide legal counsel on U.S. and international sanctions and export control laws and regulations, including OFAC sanctions programs, the Export Administration Regulations (EAR), the International Traffic in Arms Regulations (ITAR), and other applicable trade control regimes

• Advise on the application of sanctions and export controls to Anthropic's products, services, business operations, and commercial transactions

• Support the development and maturation of Anthropic's sanctions and export controls compliance programs, including policies, procedures, and controls

• Partner with Integrity, Compliance, Security, Finance, People, and Operations teams to implement scalable trade compliance solutions as the company grows

• Advise on sanctions and export control considerations in customer and third-party transactions, including contract negotiations and due diligence

• Support customer-facing teams in addressing trade compliance queries from commercial partners and enterprise customers

• Monitor legal and regulatory developments in sanctions and export controls, and advise leadership on their implications for Anthropic's business

• Manage engagement and communications with relevant government agencies, including BIS, OFAC, and other authorities as needed

• Support internal investigations and voluntary disclosures relating to potential trade compliance matters

• Develop and deliver training to employees on sanctions and export control requirements

• Advise on the intersection of trade compliance and national security law in coordination with Anthropic’s national security legal counsel, including on matters where sanctions or export control considerations overlap with broader security concerns relating to frontier AI

You may be a good fit if you have:

• A JD and active membership in at least one U.S. state bar

• At least 10-12 years of experience advising on U.S. sanctions and export control laws, with a strong understanding of OFAC sanctions programs, the EAR, and related regulatory frameworks

• Experience advising technology companies on trade compliance matters, particularly in areas such as cloud computing, AI, semiconductors, or other emerging technologies subject to U.S. export controls

• Experience building or maturing trade compliance programs in a high-growth or scaling environment

• Ability to provide practical, business-oriented legal advice in a fast-paced environment, including in areas without established precedent

• Experience engaging with government authorities such as BIS, OFAC, and DDTC, including on licensing, interpretive guidance, or enforcement matters

• Ability to excel at cross-functional collaboration and effectively communicate complex legal concepts to technical, compliance, and business teams

• Comfort with ambiguity and sound judgment in novel or evolving regulatory areas

• Passion about responsible AI development and Anthropic's mission

Strong candidates may have:

• A mix of law firm and in-house experience

• Experience at a hyper-scaling tech company or in a fast-paced environment

• Familiarity with non-U.S. export control and sanctions regimes (e.g., EU, UK)

• Experience at or working with closely with OFAC, BIS, DDTC, or other government agencies responsible for administering trade controls

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At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially.

As an Applied Research Engineer at Labelbox, you will be at the forefront of developing cutting-edge systems and methods to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers. Your role will involve designing and implementing advanced systems that align human feedback into AI training processes, such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), etc. You will also work on innovative techniques to measure and improve human data quality, and develop AI-assisted tools to enhance the data labeling process.

Your Impact

• Advance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately.

• Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training.

• Increase efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy.

• Shape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment.

• Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness.

• Bridge research and real-world application by integrating breakthroughs into Labelbox’s product suite, making human-AI alignment techniques scalable and impactful for users.

• Drive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models.

• Contribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI.

• Stay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping Labelbox at the cutting edge.

• Establish Labelbox as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry's approach to human-centric AI development.

What You Bring

• A strong foundation in AI and machine learning, backed by a Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related field.

• Proven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications.

• Expertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability.

• A deep understanding of frontier AI models,such as large language models and multimodal models,and the human data strategies needed to optimize them.

• Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions.

• A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community.

• The ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes.

• Strong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches.

• Exceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders.

Labelbox Applied Research

At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios.

We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.

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We believe skill with AI is fundamental to human agency. Education Labs sits inside Product Research, which means we build learning products with a front-row seat to what's coming. We're close to the people shaping Claude's next capabilities, and our job is to make sure the world can actually use them.

Responsibilities

Build at the frontier - Co-develop vision and own strategy and execution for AI-native learning products , the adaptive systems, assessments, and in-product experiences that will define how people learn with and about frontier AI Work closely with research teams to understand emerging capabilities and what they unlock for learners , you're translating research into product, not waiting for a spec Prototype and experiment to validate ideas quickly, using Claude and our internal tools as building blocks Anticipate how capability shifts change the product and build with that trajectory in mind Stay close to learners , run user research, watch real people move from "I don't understand this" to "I could teach this," and let what you observe reshape what we build

Be a thought partner Push the team's thinking on what education should look like as AI capabilities accelerate , help us spot what we're missing, not just execute what we've already decided Bring product rigor to a team that's scaling fast: clear priorities, sharp tradeoffs, honest metrics that connect learning to real behavior change Act as a bridge between research, product, GTM, marketing, comms, and the education team, translating in all directions

See the whole picture Collaboratively define success metrics grounded in demonstrated understanding, skill progression, and lasting agency , not time-on-site or completion counts Keep a hand in the success of adjacent team efforts, helping the overall education portfolio work as a system rather than a collection of projects Partner across Anthropic , product teams, research, GTM, societal impacts, marketing , to keep education woven into how we ship and scale Run the program, not just the product: drive stakeholder alignment across technical and non-technical partners, keep workstreams on track, and own the operational rhythm that turns strategy into shipped work

You may be a good fit if you have

5+ years in product management, with a track record of shipping products from zero to one and seeing them through to real impact Technical fluency , you're comfortable with AI tools, can prototype with Claude, and hold your own in conversations with researchers and engineers Genuine curiosity about frontier AI , you follow what's emerging, you play with new capabilities, and you have opinions about where things are heading Comfort with ambiguity and wide scope , you make good calls with incomplete information and you're not precious about where your job ends A track record as a force multiplier on small teams , you make the people around you more effective, not just your own roadmap Strong written and verbal communication , you can write a crisp spec, present to leadership, and synthesize messy stakeholder input into a clear direction Conviction that education should build agency, not dependency , you want to teach people to think with AI, and you believe that matters

Strong candidates may also have

Experience working closely with research or applied science teams, or a background that makes you fluent in how research becomes product Background in learning products, developer education, or curriculum design Founder experience or time at an early-stage company where scope was wide and you wore many hats Familiarity with how people actually learn , learning science, instructional design, or strong instincts from having taught something yourself Experience building with LLMs as core product infrastructure, not just as a feature

What this role is not

This is a hands-on IC product, project, and program management role. You'll shape strategy, push the team's thinking, and have real influence over what education at Anthropic becomes, and coordinate complex execution across multiple stakeholders and teams , but it doesn't involve people management. If you're looking to immediately lead a team, this isn't the right fit. If you want broad scope and high autonomy as a builder, it might be.

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This is a foundational, global role sitting at the intersection of Partnerships, Finance, and Legal. You'll serve as the point of resolution for questions of deal attribution, incentive eligibility, and channel conflict, and codify decision criteria so the program scales consistently.

Responsibilities:

• Design and own the commercial framework spanning all partner channels and geographies , incentive structures, discount and margin frameworks, eligibility criteria, rules of engagement, and deal registration protection

• Run quarterly incentive qualification and governance: validate threshold attainment, resolve attribution disputes, and determine payout eligibility before handoff to Finance

• Adjudicate channel conflict, contested deal registrations, and dual-partner claims against documented criteria - and evolve those criteria as new edge cases surface

• Govern partner investment programs (market development funds, co-investment funds, and similar), deciding eligible activity, matching ratios, and at-risk vs. opportunistic deployment

• Track bilateral obligations with strategic partners , both what Anthropic has committed and what partners owe back , and trigger cure, renegotiation, or escalation when commitments slip

• Act as the primary commercial interface to Legal and Finance, translating partner business needs into contract terms, rebate structures, and localised commercial instruments

• Maintain the authoritative source document for partner commercial terms, holding the line against ad-hoc carve-outs while knowing when the framework genuinely needs to evolve

• Codify decision criteria so that exception handling scales beyond you as the partner program grows

You may be a good fit if you have

• 12+ years in partner operations, channel operations, commercial strategy, deal desk, or pricing - with direct ownership of multi-channel commercial frameworks across system integrators, resellers, and/or marketplace partners

• Hands-on experience managing market development funds, partner co-investment programs, or equivalent partner funding vehicles

• A track record of running incentive governance at a regular cadence, where your calls held up under pushback from both sales teams and partners

• Commercial and legal fluency: you've drafted commercial terms, rebate structures, and discount frameworks, and worked as the translator between business needs and Legal/Finance constraints

• Demonstrated ability to scale exception handling , turning one-off judgment calls into documented criteria that others can apply consistently

• Comfort operating as a global individual contributor across time zones, with occasional travel to partner and regional team locations

• Sound judgment and a calm, decisive approach when two parties both have a reasonable case and someone has to make the call

Strong candidates may also have

• Experience standing up partner commercial frameworks from zero at a high-growth technology company

• Background in consumption-based or usage-based business models and the incentive design challenges they create

• Exposure to international partner programs requiring localised pricing, legal instruments, and currency/payment terms

• Familiarity with partner relationship management (PRM) systems and how commercial rules get operationalised in tooling

• Interest in the responsible deployment of frontier AI and how partner ecosystems shape who gets access to it

The annual compensation range for this role is £195,000-£225,000 GBP.

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You'll drive the adoption of safe, frontier AI by securing strategic deals with manufacturing brands. You'll leverage your consultative sales expertise in the manufacturing sector to propel revenue growth while becoming a trusted partner to manufacturing stakeholders, helping them embed and deploy AI while uncovering its full range of capabilities in production, supply chain, and operations.

In collaboration with GTM, Product, and Marketing teams, you'll continuously refine our value proposition, sales methodology, and market positioning to resonate with manufacturing decision-makers.

Responsibilities:

• Win new business and drive revenue for Anthropic within the manufacturing sector. Navigate complex manufacturing organisations to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close

• Design and execute innovative sales strategies tailored to manufacturing procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze manufacturing market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns

• Spearhead market expansion by identifying new use cases within production teams, engineering departments, and operations centres. Collaborate cross-functionally to differentiate our offerings for manufacturing applications

• Navigate complex manufacturing stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus

• Inform product roadmaps and features by gathering feedback from users and conveying manufacturing market needs. Provide insights that strengthen our value proposition for manufacturing

• Continuously refine the manufacturing sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency

You may be a good fit if you have:

• 8+ years of B2B sales experience in SaaS, API solutions, or emerging technologies.

• A track record of managing complex sales cycles within manufacturing organisations and securing strategic deals by understanding both technical requirements and manufacturing use cases

• Demonstrated ability to navigate manufacturing organisational structures and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments

• Extensive experience negotiating complex agreements within manufacturing procurement frameworks and policies

• Proven experience exceeding revenue targets by effectively managing an evolving pipeline and sales process

• Excellent communication skills and the ability to present confidently to various manufacturing audiences, from plant managers and engineers to senior executives

• Deep understanding of manufacturing buying cycles, decision-making processes, and key pain points

• A strategic, analytical approach to assessing the manufacturing market combined with creative, tactical execution to capture opportunities

• A passion for and/or experience with advanced AI systems and their applications. You feel strongly about ensuring frontier AI systems are developed safely and ethically for manufacturing use

The annual compensation range for this role is £280,000-£330,000 GBP.

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Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

We’re looking for prompt and context engineers to join our product engineering team to help build AI-first products, features, and evaluations. Your mission will be to bridge the gap between model capabilities and real product experience, working with product teams to build consistent, safe, and beneficial user experiences across all product surfaces.

You will be deeply involved in new product feature and model releases at Anthropic, combining engineering expertise with an understanding of frontier AI applications and model quality. You’ll become an expert on Claude’s behavioural quirks and capabilities and apply that knowledge to deliver the best possible user experience across models and domains. You’ll be the first resource for product teams working on Claude’s AI infrastructure: system prompts, tool prompts, skills, and evaluations.

This role requires someone who can effectively balance caring deeply about making Claude the best it can be while also supporting a wide variety of concurrent projects and efforts across many product teams.

Key Responsibilities

• Prompt Engineering Excellence: Design, test, and optimise system prompts and feature-specific prompts that shape Claude’s behaviour across consumer and API products.

• Evaluation Development: Build and maintain comprehensive evaluation suites that ensure model quality and consistency across product launches and updates.

• Cross-functional Collaboration: Partner closely with product teams, research teams, and safeguards to ensure new features meet quality and safety standards.

• Model Launch Support: Play a critical role in model releases, ensuring smooth rollouts and catching regressions before they impact users.

• Infrastructure Contribution: Help build and improve the frameworks and tools that allow teams to develop and test prompts and features with confidence.

• Knowledge Transfer: Mentor product engineers on prompt engineering best practices and help teams build their first evaluations.

• Rapid Iteration: Work in a fast-paced environment where model capabilities advance daily, requiring quick adaptation and creative problem-solving.

What We’re Looking For

Required Qualifications

• 5+ years of software engineering experience with Python or similar languages.

• Demonstrated experience with LLMs and prompt engineering (through work, research, or significant personal projects).

• Strong understanding of evaluation methodologies and metrics for AI systems.

• Excellent written and verbal communication skills – you’ll need to explain complex model behaviours to diverse stakeholders.

• Ability to manage multiple concurrent projects and prioritise effectively.

• Experience with version control, CI/CD, and modern software development practices.

Preferred Qualifications

• Experience with Claude or other frontier AI models in production settings.

• Background in machine learning, NLP, or related fields.

• Experience with A/B testing and experimentation frameworks (e.g., Statsig).

• Familiarity with AI safety and alignment considerations.

• Experience building tools and infrastructure for ML/AI workflows.

• Track record of improving AI system performance through systematic evaluation and iteration.

You Might Thrive in This Role If You…

• Get excited about the nuances of how language models behave and love finding creative ways to improve their outputs.

• Enjoy being at the intersection of research and product, translating cutting-edge capabilities into user value.

• Are comfortable with ambiguity and can define success metrics for novel AI features.

• Have a strong sense of ownership and drive projects from conception to production.

• Are passionate about building AI systems that are helpful, harmless, and honest.

• Thrive in collaborative environments and enjoy teaching others.

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren’t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you’re interested in this work.

Your safety matters to us. To protect yourself from potential scams, we want to remind you that we will never ask you to pay any fees for the hiring process. If someone contacts you claiming to be from Anthropic and asks for money, please report it to us immediately.

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Responsibilities:

• Win new business and drive revenue for Anthropic within the Insurance sector. Navigate complex institutions to reach key decision-makers, educate them about our services, and help them succeed with Anthropic. You'll own the full sales cycle, from first outbound to close

• Design and execute innovative sales strategies tailored to Insurance procurement cycles and budgeting processes to meet and exceed revenue quotas. Analyze market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities and campaigns

• Spearhead market expansion by identifying new use cases within Insurance departments, research centers, and administrative offices. Collaborate cross-functionally to differentiate our offerings for Insurance applications

• Navigate complex stakeholder ecosystems including executives, administrators, IT departments, and procurement offices to build consensus

• Inform product roadmaps and features by gathering feedback from users and conveying Insurance market needs. Provide insights that strengthen our value proposition for Insurance

• Continuously refine the Insurance sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency

You may be a good fit if you have:

• 5+ years of B2B sales experience in Insurance technology, preferably in SaaS or emerging technologies

• A track record of managing complex sales cycles within Insurance organizations and securing strategic deals by understanding both technical requirements and use cases

• Demonstrated ability to navigate Insurance bureaucracies and procurement processes, building consensus among diverse stakeholders including executives, administrators, and IT departments

• Extensive experience negotiating complex agreements within Insurance procurement frameworks and policies

• Proven experience exceeding revenue targets in the Insurance sector by effectively managing an evolving pipeline and sales process

• Excellent communication skills and the ability to present confidently to various audiences within Insurance

• Deep understanding of Insurance buying cycles, decision-making processes, and key pain points

• A strategic, analytical approach to assessing the Insurance market combined with creative, tactical execution to capture opportunities

• A passion for and/or experience with advanced AI systems and their applications in Insurance. You feel strongly about ensuring frontier AI systems are developed safely and ethically

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$290,000 - $435,000USD

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Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.

Responsibilities

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers, such as MCP servers, sub-agents, and agent skills, that will be used in production workflows.
• Provideษ deployment support for Anthropic products in enterprise environments.
• Identify and codify reusable deployment patterns and provide information to our Product and Engineering teams.
• Maintain a deep understanding of the latest developments in LLM capabilities, implementation models, and product development technology stacks.
• Establish long-term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Frequently travel (25-50%) to customer sites to build personal relationships with them.
• Be a champion of the Anthropic mission on the ground.

Profile

• You have more than 4 years of experience in a technical customer-facing role, such as a Forward Deployed Engineer or a Software Engineer with a customer-facing background. Former technical founders are also encouraged to apply.
• You have experience in production with LLMs, including advanced engineering of prompts, development of agents, evaluation frameworks, and large-scale deployment.
• You have solid programming skills with a mastery of Python (and ideally one or more other languages such as TypeScript, Java, etc.) and experience shipping production applications.

High action capacity, able to navigate the ambiguity that characterizes complex organizations.

• High cooperation spirit for inter-organizational collaboration, balancing competing priorities with integrity.
• Passion for promoting safe and beneficial AI systems through creative technical applications.
• Solid communication skills to lead exploratory discussions with customers and convey technical concepts to various stakeholders while maintaining a humble and collaborative attitude.
• Experience in the finance, healthcare/life sciences, or another industry is an asset.
• Experience with enterprise IT systems and/or AI deployment models is an asset.

As a member of the Applied AI team at Anthropic, you will be a Forward Deployed Engineer (FDE) who embeds directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems. Our FDEs engage with customers to accelerate the adoption of existing products and create new applications built on our models.

Working closely with our Post-Sales, Product, and Engineering teams, you'll combine engineering expertise, an understanding of frontier AI applications, and customer-facing skills to understand customer workflows and develop innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.

You will sit at the frontier of enterprise AI deployments and serve as one of our founding FDEs who helps to shape our forward-deployed motion. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. This is a significant responsibility: you’ll play a key role in championing our mission in the enterprise.

Responsibilities

• Work within customer systems to build production applications with Claude models, ensuring that these products meet customer requirements.
• Deliver technical artifacts for customers, such as MCP servers, sub-agents, and agent skills, that will be used in production workflows.
• Provide deployment support for Anthropic products in enterprise environments.
• Identify and codify reusable deployment patterns and provide information to our Product and Engineering teams.
• Maintain a deep understanding of the latest developments in LLM capabilities, implementation models, and product development technology stacks.
• Establish long-term relationships with customers and proactively identify new opportunities for AI deployment throughout the lifecycle of an engagement.
• Frequently travel (25-50%) to customer sites to build personal relationships with them.
• Be a champion of the Anthropic mission on the ground.

Profile

• You have more than 4 years of experience in a technical customer-facing role, such as a Forward Deployed Engineer or a Software Engineer with a customer-facing background. Former technical founders are also encouraged to apply.
• You have experience in production with LLMs, including advanced engineering of prompts, development of agents, evaluation frameworks, and large-scale deployment.
• You have solid programming skills with a mastery of Python (and ideally one or more other languages such as TypeScript, Java, etc.) and experience shipping production applications.

High action capacity, able to navigate the ambiguity that characterizes complex organizations.

• High cooperation spirit for inter-organizational collaboration, balancing competing priorities with integrity.
• Passion for promoting safe and beneficial AI systems through creative technical applications.
• Solid communication skills to lead exploratory discussions with customers and convey technical concepts to various stakeholders while maintaining a humble and collaborative attitude.
• Experience in the finance, healthcare/life sciences, or another industry is an asset.
• Experience with enterprise IT systems and/or AI deployment models is an asset.

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Location

San Francisco

Employment Type

Full time

Department

Technical Program Management

Compensation

• $207K – $335K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Trustworthy AI team is investing in external assurances to build out a robust safety ecosystem. This includes enabling third party assessments for OpenAI’s flagship launches, piloting new assurance mechanisms like safety compliance reviews, and incorporating independent expert input as evidence for critical safety decisions. This role requires a blend of partnership management, cross functional coordination, an understanding of AI safety research and evaluations, and strong communication skills to synthesize findings and translate into decision relevant actions.

About the Role

As a Technical Program Manager on the Trustworthy AI team, you will drive interdisciplinary programs in collaboration with external partners. This includes strategizing and executing on the vision for strategic research partnerships, and growing and managing our external assurance programs which include third party assessments and enabling independent academic research.

We’re looking for people who have experience running strategic academic collaborations and program management with technical and research teams. You will work with researchers/engineers both internal to OpenAI and as a part of the external community to initiate new projects, set ambitious goals and milestones, and drive execution across multiple teams.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Create strategic research partnerships

• Proactively identify new partners for external assurances such as high quality third party evaluators and academic research labs

• Create feedback mechanisms for translating external research into actionable product and policy recommendations

• Communicate progress, status and risk effectively to stakeholders internally and externally

• Drive tool and process improvements to improve efficiency

You might thrive in this role if you:

• Have an understanding of AI evaluations and measurements and ability to engage with technical teams on AI evaluations

• Have experience working with and managing stakeholders external to an organization, especially academic researchers

• Can create executive summaries and synthesis of technical and social science research

• Have worked cross functionally across product, research, and engineering teams

• Have an understanding and interest in frontier AI safety and policy

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Microsoft AI are looking for a talented Technical Program Manager to help bring their vision to life. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI frontier models. You'll work directly with leadership to shape the company's direction in the AI and society markets.

About the Role

As a Technical Program Manager, you will establish and operationalize AI safety, governance, and responsibility practices across the model lifecycle. You will work directly with world-leading researchers to identify risks, set responsible AI standards, and ensure that appropriate mitigations are in place before their models are released. You will collaborate with fast-paced model development teams to identify risks, develop policies and evaluations, and ensure appropriate mitigations are in place prior to deployment.

Accountabilities

• Collaborate with fast-paced model development teams to identify risks, develop policies and evaluations, and ensure appropriate mitigations are in place prior to deployment.
• Establish, improve, and operationalize foundation model governance processes, ensuring Microsoft Superintelligence addresses key risks and develops models that benefit people and society.

The Candidate we're looking for

Experience:

• Related bachelor's degree AND experience in AI policy, AI governance, or a related field OR equivalent experience.

Technical skills:

• Demonstrated experience identifying and addressing risks related to frontier AI through both technical and non-technical measures.

Personal attributes:

• Proven ability to collaborate with highly technical stakeholders, identify novel risks from technical specifications, and guide mitigation efforts.

Benefits

• Microsoft's mission is to empower every person and every organization on the planet to achieve more.
• As employees, they come together with a growth mindset, innovate to empower others, and collaborate to realize their shared goals.
• Each day, they build on their values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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What you'll do

• Context Engineering: Design, test, and optimize context strategies and system prompts that shape answer engine behavior across products, features, and use cases.
• Evaluation Systems: Build automated and semi-automated evaluation pipelines that measure model quality, catch regressions, and scale across product surfaces.
• Model Launch Support: Partner with research and engineering to validate model behavior before and during rollouts, ensuring smooth transitions with no degradation.
• Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects — for both internal and production-facing systems.
• Cross-functional Collaboration: Work closely with design, product, and research teams to translate product goals into concrete model behavior requirements.
• Knowledge Sharing: Help engineers across teams build intuition for prompt design, context engineering, and evaluation best practices.
• Staying Current: Track the latest alignment, evaluation, and prompting techniques from industry and academia, and bring the best ideas back to the team.

What you need

• Experience designing evaluations, benchmarks, or metrics for AI systems.
• Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
• Ability to manage multiple concurrent projects in a fast-moving environment.
• Strong experience with Perplexity or other frontier AI models in production settings.
• Demonstrated experience with Python — you'll prototype, debug, automate, and build systems at scale.
• 3+ years of experience working with LLMs in a product or research setting.

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