RAG + Agentic AI Lead

Codvo.ai; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Fast growth environment

Work on cutting-edge AI systems

Ownership over architectures

Job summary

Codvo.ai is seeking an experienced RAG + Agentic AI Lead in Pune District, India. This role involves building innovative AI solutions, leading a team of engineers, and ensuring the successful implementation of complex data systems.

The ideal candidate will have over 7 years of experience in AI/ML with a focus on RAG and agentic workflows, along with expertise in Python and FastAPI. Join us to influence cutting-edge technology and grow in a fast-paced environment.

Qualifications

• 7+ years of experience in AI/ML engineering with a strong focus on RAG and agentic AI.
• Proven track record in building production-grade AI systems and architecture.
• Experience with document parsing and ETL pipelines.

Responsibilities

• Build end-to-end RAG pipelines and document ingestion pipelines.
• Implement LangGraph-based agentic workflows and optimize vector search systems.
• Lead and mentor a team of AI/ML engineers.

Skills

RAG Engineering

Agentic AI

Vector & Search

LLM Ops

Backend & Infra

Data Engineering

Security & Governance

Tools

Python

FastAPI

Docker

Qdrant

OpenSearch

Job description

RAG + Agentic AI Lead

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 optimize 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.
• Lead and mentor a team of AI/ML engineers, providing technical guidance, architectural direction, and code reviews.

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

Experience: 7+ Years