AI Integration Engineer
Knowledge-base-grounded AI assistants, retrieval pipelines, prompt engineering at production scale. LLM cost and quality monitoring. Integration with client CMS, CRM, and support stacks.
About the role
OpenSource Technologies is looking for an AI Engineer to help our clients move AI from prototype to production. You'll design, build, and ship LLM-powered features, RAG pipelines, and ML services that run reliably at scale — not demos, but systems real users depend on. You'll work directly with clients and our engineering team, owning problems end to end.
What you'll do
- Build production AI features: LLM integrations, retrieval-augmented generation (RAG), agents, and evaluation pipelines.
- Design and ship ML/AI services — from data pipelines and model selection to deployment, monitoring, and cost optimization.
- Turn ambiguous client problems into scoped, measurable solutions with clear success metrics.
- Write clean, tested, well-documented code and own it through to production and beyond.
- Collaborate with full-stack, DevOps, and QA teammates to integrate AI into existing apps and workflows.
- Stay current with the fast-moving AI landscape and bring practical, cost-aware recommendations to the table.
What we're looking for
- 3+ years of software engineering experience, with at least 1–2 years building AI/ML or LLM-powered systems.
- Strong Python; comfortable with production codebases (testing, code review, CI/CD).
- Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar) and frameworks for RAG/agents.
- Solid understanding of embeddings, vector databases, prompt design, and evaluation.
- Experience deploying services to the cloud (AWS/GCP/Azure), with an eye on latency, reliability, and cost.
- Clear communicator who can explain trade-offs to both engineers and non-technical stakeholders.
Nice to have
- Experience with fine-tuning, model serving, or MLOps tooling.
- Full-stack familiarity (TypeScript/Node, React) to integrate AI end to end.
- Background in a client-services or consulting environment.
- Contributions to open-source AI/ML projects.
Why OST
- Work on production AI for real clients across multiple industries — variety, ownership, and impact.
- A senior team that values clean engineering, direct communication, and shipping things that actually work.
- Flexible, remote-friendly setup with the autonomy to do your best work.
How to apply
Send a short note about a production AI system you've shipped (what it did, your role, and one hard trade-off you made) along with your resume via the Apply button. We respond to every legitimate application within 5 business days.