Description

Reusable launch systems are the key to seamlessly connecting Earth and space. Just as our rocket systems are designed to be reliable, automated, and intelligent, the internal tools that power our engineering and business operations must embody those same principles to help our teams move faster, work smarter, and stay focused on the mission.

We are looking for a Senior AI Infrastructure Engineer to design, build, and deploy AI-powered tooling across Stoke’s internal systems. As part of our IT Internal Tooling team, you will identify high-leverage opportunities to apply AI - including large language models, agentic systems, retrieval pipelines, and intelligent automation - and turn them into production-grade tools that meaningfully accelerate the people building rockets.

This role requires deep technical expertise in modern AI engineering, software development, and systems integration, combined with a strong product instinct for what to build, what not to build, and how to ship AI tooling that actually works. You will work closely with engineers, operators, and business stakeholders across Stoke to understand their workflows, identify where AI can remove friction or unlock new capabilities, and design and implement robust solutions end-to-end. This is a high-impact role where your work directly shapes how our company operates and how quickly our teams can deliver.

You must be ready to stay focused, move quickly, self-direct, and learn on the fly.

Responsibilities

• Design, develop, and deploy AI-powered internal tools end-to-end – from initial use-case discovery and prototyping through production deployment, monitoring, and iteration
• Build LLM-powered applications, agents, retrieval-augmented generation (RAG) systems, and intelligent workflow automations that integrate with Stoke’s internal systems and data sources
• Partner with stakeholders across engineering disciplines, manufacturing, supply chain, finance, and other teams to identify high-leverage opportunities for AI tooling and translate them into clear technical requirements
• Evaluate and select foundation models, frameworks, and platforms; build robust prompt, evaluation, and guardrail systems; and make pragmatic build-versus-buy decisions
• Develop and maintain the AI engineering stack used by the team, including model gateways, vector stores, evaluation harnesses, observability, and deployment pipelines
• Implement rigorous evaluation, testing, and monitoring practices for AI systems, including offline evals, online metrics, regression tracking, and human-in-the-loop review
• Design and implement integrations with internal systems and data including; telemetry data, systems requirements, document stores, code repositories, and business applications – using APIs, webhooks, and event-driven patterns
• Apply strong security, and compliance practices to AI tooling, including data handling, access controls, prompt injection defenses, and ITAR/export-control considerations
• Operate AI services in production, including capacity planning, cost optimization, latency tuning, and incident response
• Produce clear technical documentation, runbooks, and architectural decision records; mentor team members on applied AI best practices and help raise the bar across the organization

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
• Combined 5–8 years of experience in software engineering, applied AI/ML, or related roles, with at least 2 years building and shipping production AI or LLM-powered systems
• Proven track record of designing, deploying, and operating AI-powered applications at scale in a production environment
• Strong proficiency in at least one modern language commonly used in AI tooling (e.g., Python, TypeScript, Go)
• Deep, hands-on experience with modern LLM tooling and patterns, including prompt engineering, function/tool calling, agents, RAG, and structured output
• Working knowledge of one or more major foundation model providers (e.g., Anthropic, OpenAI, AWS Bedrock, Azure OpenAI) and the trade-offs between them
• Strong software engineering fundamentals: testing, code review, CI/CD, version control, observability, and clean API design
• Experience integrating with enterprise systems via REST APIs, webhooks, message queues, and event-driven architectures
• Solid understanding of evaluation methodologies for AI systems, including offline evals, golden datasets, and online quality metrics
• Strong understanding of AI security and privacy concerns, including data leakage, prompt injection, model misuse, and least-privilege data access
• Excellent communication skills and the ability to translate fuzzy business problems into concrete, shippable AI solutions

Preferred Qualifications

• Experience building agentic systems with multi-step tool use, planning, and long-running workflows
• Experience with vector databases, embedding models, hybrid search, and advanced retrieval techniques
• Experience deploying AI workloads on AWS (Bedrock, Lambda, ECS/Fargate) or comparable cloud platforms
• Experience with model fine-tuning, distillation, or training custom models for narrow internal use cases
• Familiarity with ITAR, export controls, or other regulated-data environments and the implications for AI tooling
• Experience with MCP (Model Context Protocol) servers, internal developer platforms, or building reusable AI infrastructure for other engineers
• Background in IT, internal tools, or digital transformation functions, with a track record of successful enterprise software rollouts
• Passion for learning new technologies and sharing knowledge with teammates

Benefits

• Equity – We know that our employees are the reason we succeed. To give everyone a stake in our future, we are pleased to offer equity in the form of stock options to all regular, full-time employees. 
• Comprehensive benefits program including subsidized medical, dental, and vision insurance 
• Company-paid life and disability insurance 
• 401(k) plan with employer match 
• 4 weeks’ Paid Time Off  
• Holidays – 10 days (including an end-of-year closure) 
• Paid Family/Parental Leave  
• On-site gym or monthly wellness stipend (depending on location) 
• Dog friendly offices! 

Compensation

Target Levels:

• Level 4 Range: $192,885 - $289,380
• Level 5 Range: $231,525 - $347,235

Our job posts are intentionally written to attract a wide variety of experience levels, and we make decisions about the right fit on a per-candidate basis. 

Your actual level and base salary will be decided based on your specific experience and skill level.