AI Engineer (Vector Database)

Optomi, in partnership with a leading enterprise organization, is looking for an AI Engineer – Generative AI & RAG.

Position Summary

Optomi is seeking a hands-on AI Engineer to design, build, test, and support Generative AI applications using Retrieval-Augmented Generation, vector databases, and agentic AI workflows. This role is focused on executing and delivering working, production-ready AI solutions rather than serving as a high-level solution architecture lead. The ideal candidate demonstrates initiative, solves complex technical problems, and can quickly learn and apply emerging AI technologies. Experience building Text-to-SQL solutions is highly preferred.

What the right candidate will enjoy:

• Building production-ready solutions with cutting-edge Generative AI technologies
• Solving complex problems involving enterprise data, retrieval, and agentic workflows
• Designing and optimizing vector search and RAG solutions
• Collaborating with technical and business stakeholders
• Helping establish reusable AI-development practices across an engineering team
• Evaluating and improving the accuracy, reliability, performance, and cost of AI applications

What type of experience does the right candidate have:

• Hands-on experience building and deploying production Generative AI applications using RAG
• Strong experience designing vector databases and optimizing vector search
• Production-grade Python experience with async programming, Pydantic, pytest, and modern packaging tools
• Experience building agentic workflows using LangChain and/or LangGraph
• Strong knowledge of chunking, embeddings, metadata design, and retrieval strategies
• Experience ingesting data from platforms such as SQL Server and Snowflake into vector or search databases
• Experience supporting incremental loads and evolving schemas
• Daily experience using AI-assisted development tools such as Claude Code, GitHub Copilot, Codex, or Windsurf
• Experience with Git-based workflows and CI/CD
• Ideally, experience building and validating Text-to-SQL solutions

What the responsibilities are of the right candidate:

• Design, build, test, and support production-ready Generative AI applications
• Develop RAG solutions that retrieve relevant enterprise information and generate accurate, grounded responses
• Design and optimize vector database indexes, schemas, filters, and search queries
• Select and implement appropriate chunking, embedding, metadata, and retrieval strategies
• Build data-ingestion pipelines connecting relational platforms such as SQL Server and Snowflake with search and vector stores
• Develop agentic workflows using LangChain and/or LangGraph
• Implement state management, conditional routing, memory, checkpointing, and tool-calling capabilities
• Create automated tests and evaluation processes for AI applications
• Use AI-assisted development tools to accelerate delivery while maintaining code quality
• Establish reusable agent instructions, repository rules, and development context for the broader engineering team
• Participate in Git-based code reviews, CI/CD, deployment, and production support
• Monitor and improve the accuracy, performance, reliability, and cost of AI solutions
• Collaborate with technical and business stakeholders to translate use cases into working applications