This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

• Agent Development Wiz
• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

• Infrastructure Guru
• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role

• Customer Product Whisperer
• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

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.

• Deep Research for Due Diligence
• Churn Prediction
• Data Extraction Voice Agent

Compensation

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.

Pay Transparency

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

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You'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.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Customer Integration & Deployment

Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements.

Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs).

Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows.

Deploy and configure AI models and agents within customer security and compliance boundaries.

AI Agent Development

Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation.

Architect multi-agent systems that orchestrate between different models, tools, and data sources.

Implement evaluation frameworks to measure agent performance and iterate toward business objectives.

Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement.

Prompt Engineering & Optimization

Create sophisticated prompt engineering strategies optimized for customer-specific domains and data.

Build and maintain prompt libraries, templates, and best practices for customer use cases.

Conduct systematic prompt experimentation and A/B testing to improve model outputs.

Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate.

Leadership & Collaboration

Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts.

Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration.

Work closely with Scale's product and engineering teams to translate customer needs into product improvements.

Document technical architectures, integration patterns, and best practices.

Problem Solving & Innovation

Debug complex technical issues across the entire stack, from data pipelines to model outputs.

Rapidly prototype solutions to unblock customers and prove out new use cases.

Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems.

Identify opportunities for productization based on common customer patterns.

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Microsoft AI are looking for a talented Member of Technical Staff - Prompt Engineer at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Prompt Engineer, you'll craft the foundations that enable meaningful human-AI partnerships. You'll design and develop prompting techniques for emotional and intellectual use cases, establish frameworks for AI companions to navigate complex social and ethical situations with nuance and care, and create evaluations to measure both technical/practical performance and non-deterministic performance like EQ.

Accountabilities

• Design & develop prompting techniques for emotional and intellectual use cases
• Establish frameworks for AI companions to navigate complex social and ethical situations with nuance and care

The Candidate we're looking for

Experience:

• 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

Technical skills:

• Experience with large language models
• Familiarity with both quantitative metrics and qualitative assessment methods

Personal attributes:

• A wonderful writer who loves words, storytelling, or linguistics
• Effective written communication skills: able to convey complex information clearly, concisely, and effectively for various audiences

Benefits

• Software Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year
• Certain roles may be eligible for benefits and other compensation

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