Description :

AI Engineer / Agentic AI Developer

Location : Bangalore / Kolkata

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 :

1. OpenAI

2. Azure OpenAI

3. AWS Bedrock

4. Google Gemini

5. Google AI Studio

6. Claude

7. Mistral

Agentic AI & Automation:

i. Tools : LangChain, LangGraph, LangFlow, Copilot Studio, n8n, ADK (Agent Development Kit)

Vector Search & RAG

ii. 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 :

a. 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