Role & responsibilities

1. Design and build production-grade agentic systems end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability
2. Build and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets
3.Integrate and abstract across multiple LLM providers OpenAI, Anthropic, Vertex AI, and open-source models — with fallback routing, token, cost, and latency management
4. Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring
5. Embed directly with client engineering teams to design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs
6. Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster
7. Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness present findings and recommendations to client stakeholders in business terms

📌 AI and Java Full Stack Developer (Hyderabad)
🏢 Lecan Solutions
📍 Hyderabad