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 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.
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
- Halluci
📌 RAG + Agentic AI Engineer (Pune)
🏢 Codvo.ai
📍 Pune