Quick Summary
Overview
RAG + Agentic AI Lead
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.
Technical Tools
dockerelasticsearchfastapipythonci-cdcode-reviewcustomer-supportetlmicroservices
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
Location & Eligibility
Where is the job
Pune, India
Remote within one country
Who can apply
IN
Listing Details
- First seen
- May 6, 2026
- Last seen
- July 21, 2026
Posting Health
- Days active
- 75
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- July 21, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
External application · ~5 min on codvo-team's site
Please let codvo-team know you found this job on Jobera.
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