Software Engineer 3 - GenAI

Overview

Build and scale Energy Assistant, a GenAI assistant embedded in utility web portals and mobile apps that answers customer questions about usage, bills, appliances, rate plans, and savings through a multi-agent system built on LangGraph.

What you'll do

• Design and build production multi-agent systems: supervisor/router and specialist agents, LangGraph workflows, tool calling, conversation memory, and checkpointing.
• Build typed tool contracts and data-access layers over Bidgely APIs so the LLM explains results instead of generating numbers.
• Develop RAG pipelines for utility tariff and knowledge retrieval, with tenant-isolated embeddings and retrieval.
• Manage latency, reliability, and cost: caching, prewarming, retries, circuit breakers, and model routing across small and large model tiers.
• Implement guardrails for prompt injection, scope control, authorization, tenant isolation, and data management.
• Build observability and evaluation hooks with LangSmith, and collaborate with SDETs on evaluation datasets, regression suites, and release criteria.
• Debug agent failures in production using traces, logs, and metrics, and drive root-cause fixes.
• Support streaming (WebSocket/SSE) and widget integration with front-end teams.
• Lead design and code reviews, set engineering standards, and mentor SDE1 and SDE2 engineers.
• Communicate designs, trade-offs, and progress to engineering, product, and leadership.

What you'll need

• 6–10 years of software engineering experience, including at least 1–2 years building and shipping LLM or GenAI features in production.
• Strong Python skills and good working knowledge of Java.
• Hands-on experience with LangChain, LangGraph, or similar agent orchestration frameworks.
• Experience with LLM APIs (OpenAI, Anthropic, Amazon Bedrock), prompt design, tool/function calling, and structured outputs.
• Experience building RAG systems with embeddings and vector stores (e.g., pgvector).
• Strong backend and API design skills, with experience building scalable, low-latency services.
• Experience with AWS, containers (EKS), PostgreSQL, Redis, and CI/CD.
• Experience with evals, LLM-as-judge, or AI observability tools such as LangSmith.
• Strong system design, analytical, and communication skills.

Nice to have

• Experience with time-series, IoT, or smart meter data, or the energy and utilities domain.
• Experience with voice or IVR GenAI products.
• Experience with multi-tenant SaaS solutions, security, and data-privacy enhancements for LLM applications.

Details

• Location: India Head Office (Bengaluru engineering center).