Senior AI Engineer
Build full-stack AI systems including agentic workflows, RAG pipelines, and production infrastructure for mental healthcare applications. Requires 2+ years software engineering experience and 1+ year with LLMs or agentic AI.
Senior AI Engineer
Designs and builds LLM-based AI automation tools, data pipelines, and agentic workflows to transform business processes. Requires 6+ years software engineering with 2+ years AI/LLM production experience, strong Python, and data engineering skills.
170k – 200kSeattle, WAML EngineeringOnsite6+ YOE
About the role
What you'll do
- Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
- Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
- Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
- Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
- Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
- Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
- Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture
What we're looking for
- 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
- Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
- Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
- Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
- Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
- A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
- Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection
While not required, these are a plus:
- Experience with vector databases, embeddings, or semantic search
Our Stack
Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited) Datastores: MySQL, PostgreSQL, Snowflake Cloud: AWS Version control: Git & GitHub AI Tooling: Copilot on GitHub and Claude Code Observability: Datadog
Compensation: Anticipated base salary $170,000 - $200,000 USD annually, plus healthcare, 401(k), stock options, bonuses.
Skills
PythonLLM APIsPrompt EngineeringSQLSnowflakeAWSAirflowPrefectRAGVector DatabasesEmbeddingsPostgresDatadogTypeScriptReact
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