We are looking for a Applied AI Engineer to build and operate LLM-powered internal solutions, tools, automations, and customer-facing AI features end-to-end. We are not building AI for the sake of AI, or to follow hype or impress investors. We care about AI that works in real life and solves actual problems.
Technology choices and product decisions are not simply handed down from the top. You will have room to shape the solution, challenge assumptions, choose the right tools, and influence the result.
Build and operate LLM-powered internal solutions, tools, and automations end-to-end
Ship customer-facing AI features
Drive technical decisions from design through production rollout
Own systems in production, including monitoring, reliability improvements, and incident response participation
Build and maintain LLM evaluation workflows, including quality/safety checks, baselines, and regression detection
Partner with R&D, product, and security teams
Evaluate emerging AI technologies and patterns, and advocate adoption when justified
Qualifications
Strong software engineering fundamentals with hands-on ownership of production systems; Python required
Solid LLM application development experience, including context design, structured outputs, and orchestration
Hands-on experience with LLM evaluations, including experiment design, regression detection, gating, and observability
Experience building and operating backend services/APIs in production
Experience designing multi-service architectures and reliable integrations, including stable service contracts, retries, and failure recovery
Working knowledge of operating production databases, including schema design, indexing, migrations, and backup/restore
Hands-on experience with containerized workloads
Ability to balance output quality, latency, and cost in production AI systems
Requirements
Experience with agentic systems or RAG, including evaluation
Experience building lightweight user interfaces
Experience shipping high-adoption internal developer or operations tooling
JavaScript/TypeScript
AWS deployment and operations experience
Experience with runtime isolation and sandboxing for sensitive execution
Experience in B2B SaaS, security, compliance, or data governance contexts
Technology we use
You do not need to have experience with every tool listed below, but this is the environment we work with now:
Python, uv, FastAPI, PydanticAI
PostgreSQL, Docker, Docker Compose
AWS: EC2, ECR, S3, Lambda
Interfaces and tooling: Streamlit or similar tools, pytest, ruff, pyright, OpenTelemetry
Benefits
Fully remote work, giving you the flexibility you need in the modern world
A collaborative environment encouraging you to own your domain and implement best practices
Stable income, benefits, flexible working hours, and opportunities for promotion
Friendly and professional peers, eager to help and help you grow
A multitude of interesting challenges and opportunities