About the Role
We are looking for a hands-on AI Solutions Engineer who can take generative and agentic AI solutions from design to production. You will own the full stack: LLM orchestration, retrieval, backend services, user interface, deployment, and evaluation. This is an engineering role first. You will write production code every day and be accountable for the reliability, security, and cost of what you ship.
Key Responsibilities
Architect and build multi-agent systems with stateful orchestration, tool calling, routing, memory, and human-in-the-loop checkpoints
Design retrieval pipelines covering document parsing, chunking, embeddings, hybrid search, and reranking, grounded in governed enterprise data
Build high-performance Python backend services and streaming APIs that expose agents to web, chat, and voice channels
Develop responsive React and TypeScript front ends with real-time streaming, rich visualizations, and clean UX for business users
Deploy and operate AI workloads on the lakehouse platform and cloud, using containers, CI/CD, and infrastructure as code




Implement LLMOps practices: offline and online evaluation, LLM-as-judge scoring, tracing, prompt versioning, and regression testing
Engineer guardrails for prompt-injection defense, PII protection, output validation, and role-based data access
Optimize latency, token cost, and throughput through model selection, caching, prompt design, and parallel execution
Translate business requirements into technical designs, and document architecture decisions for review
Mentor engineers and contribute reusable components, templates, and standards to the wider team

Technical Skills
Required
Languages: Expert Python (async, typing, Pydantic, testing); working proficiency in TypeScript and SQL
LLMs and GenAI: Hands-on with frontier models (Claude, GPT, or equivalent), structured outputs, function and tool calling, context engineering, and prompt design
Agent frameworks: Production experienc

📌 Ai Solutions Engineer Bengaluru
🏢 Dautom
📍 Bengaluru