Senior Software Engineer (AI)

Role Overview We are looking for a Senior AI/ML Engineer — Generative AI & Agentic Systems to design, develop, and productionize enterprise-grade Generative AI, RAG, and Agentic AI solutions . The candidate will work closely with the AI Architect / Technical Lead to translate business requirements into scalable AI solutions and will be responsible for hands-on implementation, integration, evaluation, optimization, and deployment. This role is ideal for an engineer who enjoys building real-world AI applications using LLMs, RAG pipelines, AI Agents, tool calling, vector databases, orchestration frameworks, and cloud technologies . Key Responsibilities Design and develop production-ready Generative AI and LLM-based applications . Build scalable Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, reranking, retrieval, and contextual generation. Develop Agentic AI workflows using frameworks such as LangGraph and LangChain. Implement multi-agent workflows involving planning, reasoning, tool calling, delegation, memory, and orchestration . Integrate LLMs from OpenAI, Anthropic, Google Gemini , and other providers. Develop backend services and AI APIs using Python, FastAPI, and REST APIs . Design and implement LLM evaluation frameworks to measure accuracy, relevance, groundedness, hallucination, latency, and other quality metrics. Implement AI guardrails , validation, safety controls, structured outputs, and responsible AI practices. Work with PostgreSQL, vector databases, and graph databases to build AI knowledge systems. Containerize and deploy AI applications using Docker and cloud platforms such as Azure/AWS . Optimize LLM applications for performance, scalability, reliability, and cost. Collaborate with architects, frontend/backend engineers, DevOps, and business stakeholders. Participate in technical design, code reviews, troubleshooting, and production support. Stay current with emerging developments in LLMs, Agentic AI, RAG, open-source models, and AI infrastructure . Must-Have Skills Programming & Backend Strong hands-on experience with Python FastAPI REST API development Backend application architecture and development Generative AI & LLM LLM application development RAG architecture and implementation Prompt engineering Embeddings and semantic search Vector databases LLM integration and orchestration Experience with one or more of: OpenAI Anthropic Google Gemini Agentic AI Hands-on experience building AI Agents LangGraph and/or LangChain Tool/function calling Agent workflows and orchestration Multi-agent systems Agent state and memory management Data & Infrastructure PostgreSQL Vector databases Docker Azure and/or AWS API integration and microservices AI Quality & Security LLM evaluation RAG evaluation Hallucination detection/mitigation AI guardrails Structured output and schema validation Understanding of AI security and responsible AI practices …