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You&#39;ll work directly with customer engineering teams to integrate AI into their critical workflows.</p>\n<p><strong>Key Responsibilities</strong></p>\n<p><strong>Customer Integration &amp; Deployment</strong></p>\n<ul>\n<li>Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements</li>\n<li>Design and implement custom integrations between Scale AI&#39;s platform and customer data environments (cloud platforms, data warehouses, internal APIs)</li>\n<li>Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows</li>\n<li>Deploy and configure AI models and agents within customer security and compliance boundaries</li>\n</ul>\n<p><strong>AI Agent Development</strong></p>\n<ul>\n<li>Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation</li>\n<li>Architect multi-agent systems that orchestrate between different models, tools, and data sources</li>\n<li>Implement evaluation frameworks to measure agent performance and iterate toward business objectives</li>\n<li>Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement</li>\n</ul>\n<p><strong>Prompt Engineering &amp; Optimization</strong></p>\n<ul>\n<li>Create sophisticated prompt engineering strategies optimized for customer-specific domains and data</li>\n<li>Build and maintain prompt libraries, templates, and best practices for customer use cases</li>\n<li>Conduct systematic prompt experimentation and A/B testing to improve model outputs</li>\n<li>Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate</li>\n</ul>\n<p><strong>Technical Leadership &amp; Collaboration</strong></p>\n<ul>\n<li>Serve as the primary technical point of contact for strategic enterprise accounts</li>\n<li>Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration</li>\n<li>Provide technical training and knowledge transfer to customer teams</li>\n<li>Work closely with Scale&#39;s product and engineering teams to translate customer needs into product improvements</li>\n<li>Document technical architectures, integration patterns, and best practices</li>\n</ul>\n<p><strong>Problem Solving &amp; Innovation</strong></p>\n<ul>\n<li>Debug complex technical issues across the entire stack, from data pipelines to model outputs</li>\n<li>Rapidly prototype solutions to unblock customers and prove out new use cases</li>\n<li>Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems</li>\n<li>Identify opportunities for productization based on common customer patterns</li>\n</ul>\n<p><strong>Required Qualifications</strong></p>\n<ul>\n<li>4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design</li>\n<li>Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)</li>\n<li>Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure</li>\n<li>Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions</li>\n<li>Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Agent Development Wiz</li>\n<li>Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures</li>\n<li>Experience building and deploying AI agents or autonomous systems in production</li>\n<li>Knowledge of vector databases and semantic search systems</li>\n<li>Contributions to open-source AI/ML projects</li>\n</ul>\n<ul>\n<li>Infrastructure Guru</li>\n<li>Experience with containerization (Docker, Kubernetes) and CI/CD pipelines</li>\n<li>Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools</li>\n<li>Previous work in a devops, platform, or infra role</li>\n</ul>\n<ul>\n<li>Customer Product Whisperer</li>\n<li>Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role</li>\n<li>Domain expertise in verticals like finance, healthcare, government, or manufacturing</li>\n<li>Experience with technical enablement or teaching programs</li>\n</ul>\n<p><strong>Sample Projects</strong></p>\n<p>The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.</p>\n<ul>\n<li>Deep Research for Due Diligence</li>\n<li>Churn Prediction</li>\n<li>Data Extraction Voice Agent</li>\n</ul>\n<p><strong>Compensation</strong></p>\n<p>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.</p>\n<p><strong>Pay Transparency</strong></p>\n<p>For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000-$270,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3aedc59f-428","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale AI","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4597399005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,000-$270,000 USD","x-skills-required":["Software engineering","Data structures","Algorithms","System design","Python","ML/AI frameworks","Cloud platforms","Modern data infrastructure","Problem-solving","Communication"],"x-skills-preferred":["LLMs","Prompting techniques","Embeddings","RAG architectures","Containerization","CI/CD pipelines","Infrastructure as Code","Devops","Platform","Infra"],"datePosted":"2026-04-18T15:59:30.214Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software engineering, Data structures, Algorithms, System design, Python, ML/AI frameworks, Cloud platforms, Modern data infrastructure, Problem-solving, Communication, LLMs, Prompting techniques, Embeddings, RAG architectures, Containerization, CI/CD pipelines, Infrastructure as Code, Devops, Platform, Infra","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3e231b3e-949"},"title":"Forward Deployed AI Engineering Manager, Enterprise","description":"<p>As a Forward Deployed AI Engineering Manager on our Enterprise team, you&#39;ll be the technical bridge between Scale AI&#39;s cutting-edge AI capabilities and our most strategic customers.</p>\n<p>You&#39;ll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.</p>\n<p>This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. 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Your expertise lies in navigating complex technical challenges and delivering innovative automation solutions through intelligent system design.</p>\n<p>You bring a strong foundation in AI/ML, hands-on experience with prompt engineering, and a proven track record of integrating advanced tools across diverse platforms.</p>\n<p>You thrive in collaborative environments, adept at translating business needs into scalable, secure, and reliable technical solutions. Compliance and vulnerability management are second nature to you, and you proactively embed best practices into your development workflow.</p>\n<p>You are excited by the prospect of architecting end-to-end AI automation within the Fluids Business Unit (FBU), enhancing global user experiences and streamlining workflows for maximum impact.</p>\n<p>Your background includes MCP architectures, enterprise automation, and secure DevOps practices. You excel at integrating AI-powered tools into large-scale platforms, such as Copilot, and are driven by a relentless desire to innovate.</p>\n<p>As a leader and collaborator, you inspire those around you to strive for continuous improvement and technical excellence. You are committed to pushing the boundaries of what’s possible, ensuring the solutions you build are not only powerful but also future-ready.</p>\n<p>Designing and developing MCP-based AI tools for seamless cross-platform usage within the Fluids Business Unit.\nImplementing intelligent code generation, setup validation, automated report creation, and user-defined function (UDF) generation features.\nEnabling support for multiple LLM providers and models, ensuring portability and extensibility of AI solutions.\nIntegrating FBU’s MCP server with the organization’s centralized MCP server for unified workflow automation.\nCollaborating with the framework team to embed AI tools into the Copilot platform, enhancing enterprise productivity.\nEnsuring all tools comply with enterprise security standards, certifications, and vulnerability management practices.\nConducting rigorous security assessments and proactively mitigating vulnerabilities in AI pipelines and integrations.\nArchitecting scalable AI automation solutions for end-to-end workflows within Fluids One, optimizing for performance and reliability.\nOptimizing AI workflows for maintainability, scalability, and seamless user experience.</p>\n<p>Drive the AI transformation initiative within the Fluids Business Unit, advancing automation and intelligent system integration.\nEmpower end-to-end automation in Fluids One, reducing manual intervention and accelerating productivity.\nEnhance the organization’s Copilot platform with advanced AI-powered tools that simplify complex workflows.\nImprove enterprise security posture by embedding robust compliance and vulnerability management into AI solutions.\nFoster innovation in AI toolchain development, supporting multi-provider and multi-model orchestration for maximum flexibility.\nContribute to Synopsys’ leadership in AI-driven automation, setting industry standards for scalable and secure enterprise solutions.</p>\n<p>Bachelor’s or Master’s degree in Computer Science, 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