
Search by job, company or skills
Company Description & Culture Code
https://optima.ai/talent
The Idea
Models are a commodity. The harness is the product. The evolution loop is the moat. Anyone can call an LLM; the difference between an impressive demo and a product clients trust with their money lives in the harness (context engineering, memory architecture, tool design, runtime discipline, generative UI, observability) and in the evolution loop that tightens it over time. Optima has to feel at least as good as the best AI products people use today; Claude is the reference bar, not a lofty aspiration. That bar is not cleared with prompts. It is cleared with engineering. We need one head holding that foundation: systems-proficient enough hold production load, AI-native enough to think in agents and traces, versatile enough to ship anything else the work demands. If you know how to build the foundation a state-of-the-art AI product runs on, we're talking about you.
Role Description
We are recruiting an AI-Native Product Engineer to own the harness underneath Optima's AI product surfaces:
Who This Is For
What This Isn't
Compensation Highlights
Contact
Share something you're proud of building directly with us at [Confidential Information].
Job ID: 148375563
Skills:
Sql, Python, LangChain, embeddings, RAG architecture, SLM APIs, vector databases, Anthropic, AutoGen, LangGraph, LLM APIs, GCP Vertex AI, memory systems, IBM WatsonX, OpenAI, Cohere, LlamaIndex
Skills:
.NET, Apis, Typescript, Python, LangChain, embeddings, RAG vector databases, DevOps practices, AI observability practices, agentic workflows, AI retrieval systems, high-code stacks, Microsoft Agent Framework
Skills:
Apis, orchestration frameworks, agent-based architectures, data science skills, GenAI use cases, enterprise data sources, LLMs, hallucination analysis, retrieval, quality evaluation, cost monitoring, prompt version tracking, testing and evaluation, vector databases, embeddings, human-in-the-loop feedback, observability, prompt optimization, model fine-tuning
Skills:
API design, Grafana, Api Development, Distributed Systems, Prometheus, Kubernetes, Python, RAG pipelines, offline evaluation jobs, LLM APIs, OpenTelemetry, distributed tracing, embeddings, reranking, GCP tooling, LangChain, feature stores, ML system fundamentals, LangGraph, backend programming languages, batch pipelines, vector similarity, evaluation metrics, Vector DBs, retrieval quality, metadata systems, observability stacks
We don’t charge any money for job offers