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Senior AI Engineer

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Onsite

Senior AI Engineer

Metropolis

Senior AI Engineer

Skills

SQL QueriesData EngineeringReactTypescriptPythonJavaPostgreSQLMySQLSnowflakeGitDatadogAIScalaAWSGitHubApache Airflow

2 months ago

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Important information


Contract type:

Permanent

Salary:

$170,000 – $200,000 / year

Location:

Los Angeles, CA, USA

Work mode:

Onsite

Published on:

21 October 2026

What they need


  • Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective
  • You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond
  • This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply
  • If you want to see your work directly change how a company functions — not someday, but now — this is the role
  • 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
  • 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

Benefits

  • We subsidize high-quality health insurance coverage for full-time and hourly employees

  • Equity options - We offer ownership opportunities through stock options

  • Wellness benefits - A wellness program designed to support a variety of needs

  • Health insurance - We subsidise high-quality health insurance coverage for full-time and hourly employees

  • 401(k) match - Plan for your future with a 4% company match

  • Parental leave - Receive support prior to, during leave, and as you transition back to work

  • Time off - Unlimited PTO for salaried employees, and a generous PTO package for our hourly employees

  • Paid holidays - We observe major holidays with company-wide closures, and double hourly rates for those who work

  • Hybrid environment - Magic happens face to face, but we support a flexible working model

  • 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

  • A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional

  • 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)

  • Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

  • Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services

  • Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)

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

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