Senior AI Engineer

Metropolis•Seattle, WA

7h•Hybrid

About The Position

Metropolis is seeking a Senior AI Engineer to join their Applied AI organization, a team focused on rebuilding company operations from an AI-first perspective. This is a hands-on engineering role where the individual will design and ship AI-powered tools and automation pipelines to replace manual, repetitive work across various business functions like finance, operations, and revenue. The role involves owning systems end-to-end, from the LLM prompt layer to production deployment, and collaborating closely with Process Analysts to understand business needs and translate them into engineering specifications. The ideal candidate will see their work directly impact how the company functions immediately.

Requirements

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

Nice To Haves

Experience with vector databases, embeddings, or semantic search is a plus

Responsibilities

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