RAG + Agentic AI Engineer (India) (Remote)

Codvo.ai; Pune District; Remote; INR 1,000,000 - 1,400,000; Full time

Benefits offered by this job

Fast growth environment

Ownership over enterprise-grade architectures

Influence on platform and accelerators

Job summary

A technology solutions firm in Pune is seeking a skilled RAG + Agentic AI Engineer. You will build production-grade AI applications and retrieval systems while collaborating with architects. This role requires expertise in Python, FastAPI, and various AI frameworks, as well as a commitment to security and governance standards. If you are driven by innovation in AI, apply to be part of a fast-growing team.

Qualifications

• 5+ years of experience in AI engineering, particularly in RAG and LLM applications.
• Strong knowledge in building AI systems with data governance.

Responsibilities

• Build end-to-end RAG pipelines.
• Design multi-tenant knowledge layers.
• Architect FastAPI-based AI microservices.

Skills

Smart/component‑aware chunking

Hybrid retrieval (BM25 + dense)

LangGraph

Prompt engineering

Python

Qdrant

FastAPI

Tools

Docker

OpenSearch

CI/CD

Job description

Job Description — RAG + Agentic AI Engineer

About Us

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting‑edge technology.

About the Role

We are looking for a highly skilled RAG + LLM‑based Agentic AI Engineer to build production‑grade retrieval systems, multi‑agent workflows, and enterprise‑ready AI applications. You will work across document pipelines, model orchestration, tool‑driven agents, and governed AI systems that power Codvo’s next‑generation products

Key Responsibilities

• Build end‑to‑end RAG pipelines: smart chunking, hybrid retrieval, reranking, query rewriting.
• Implement LangGraph‑based agentic workflows with tools, planning, and self‑healing behaviors.
• Develop and optimise vector search systems (Qdrant/Weaviate/OpenSearch).
• Design multi‑tenant, ontology‑driven knowledge layers for enterprise data.
• Implement guardrails, hallucination reduction, and automated evals.
• Build and maintain document ingestion pipelines (PDF, DOCX, OCR, images).
• Architect and deploy FastAPI‑based AI microservices with caching and async execution.
• Integrate LLM systems with enterprise apps (SharePoint, CRM, databases, MCP tools).
• Ensure security, PII safety, auditability, and governance requirements are met.
• Collaborate with solution architects and domain SMEs to translate use cases into working AI systems.

Core Skills & Competencies

RAG Engineering

• Smart/component‑aware chunking
• Hybrid retrieval (BM25 + dense)
• Reranking
• Graph‑RAG basics
• Query rewriting & multi‑hop retrieval

Agentic AI

• LangGraph
• MCP tools
• Multi‑agent orchestration
• Tool‑calling workflows

Vector & Search

• Qdrant or Weaviate
• OpenSearch/Elasticsearch
• HNSW tuning

LLM Ops

• Prompt engineering
• Hallucination control
• RAG/agent eval frameworks
• Synthetic data generation

Backend & Infra

• Python, FastAPI
• Async programming
• Docker, CI/CD
• Cloud basics

Data Engineering

• Document parsing
• ETL pipelines
• Caching, batching, streaming

Security & Governance

• PII handling
• Access control
• Audit trails

Nice‑to‑Have

• Experience with Haystack, LlamaIndex, or RAG frameworks
• Fine‑tuning retrievers or small LLMs
• Ontology modeling
• Enterprise search deployments
• Agents in customer support, ops, legal, engineering

What You’ll Get

• Work on cutting‑edge agentic AI systems at production scale
• Ownership over enterprise‑grade architectures
• Fast growth environment
• Influence Codvo’s platform and accelerators