AI Engineer / Agentic AI Developer

About the job

AI Engineer / Agentic AI Developer Location: Bangalore Mode: Hybrid Job Description: • Role Overview We are seeking a highly skilled Senior AI Engineer / Agentic AI Developer to design, build, and productionize intelligent autonomous AI systems for enterprise use cases. • The ideal candidate must have strong experience in LLMs, RAG, vector databases, multi-agent orchestration, backend engineering, and cloud deployments. • This role blends AI solution engineering, agent development, and architecture. Key Responsibilities • Architect and implement AI-powered autonomous agent workflows across enterprise processes. • Design multi-agent pipelines with planning, memory, tool calling, and human-in-the-loop controls. • Build and optimize RAG pipelines (chunking, hybrid search, ranking, retrieval validation, grounding). • Develop API-driven backend services using Python (FastAPI / Flask). Integrate agents with enterprise APIs, CRMs, ERPs, ITSM systems, and productivity tools. • Deploy on Azure / AWS / GCP, ensuring scalability, observability, and security compliance. • Implement LLMOps & governance, monitoring, risk controls, evaluation, prompt versioning, and safety. • Optimize latency, cost efficiency, response confidence, and hallucination reduction. • Contribute to internal accelerators, reusable pipelines, and best-practice frameworks. • Mentor junior team members and collaborate with business, product, and engineering stakeholders. Core Technical Skills Required • Python (advanced) backend services and AI integration LLMs & Model Platforms: • OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini, Google AI Studio, Claude, Mistral Agentic AI & Automation • Tools: LangChain, LangGraph, LangFlow, Copilot Studio, n8n, ADK (Agent Development Kit) • Vector Search & RAG. • Technologies: FAISS, ChromaDB, Pinecone, Weaviate, Azure AI Search AI Development Platforms: • Azure AI Foundry, Google AI Studio, Hugging Face, Ollama (preferred) • Backend & Microservices: FastAPI / Flask / REST / GraphQL • Databases: PostgreSQL / MongoDB / Redis • Containers & CI/CD: Docker / Kubernetes / GitHub Actions / Azure DevOps Good to Have • Experience with model fine-tuning / LoRA / QLoRA / PEFT • Agent evaluation Frameworks: Ragas / DeepEval / PromptFoo • Experience with document automation pipelines (OCR, PDFs, invoices, email processing) • Familiarity with DevOps + security + RBAC implementation for AI platforms • Hands-on experience with streaming & event-driven architecture.

Requirements

• Python
• LLMs
• Backend engineering
• Cloud deployments

Preferred Technologies

• Python
• LLMs
• Backend engineering
• Cloud deployments