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Senior AI/ML Engineer

PEPAGORA (INDIA) PRIVATE LIMITED
5 - 10 Years
Coimbatore

Posted on: 11/09/2026

Job Description

Pepagora India Pvt Ltd

Senior AI - ML Engineer - Job Description

BUILD INTELLIGENCE

Location: Coimbatore - Work Mode: Work from Office

We don't need another chatbot engineer.

About Pepagora:

Pepagora is trust infrastructure for global B2B growth. We operate a verification-first ecosystem that reduces trust friction, improves deal velocity, and enables SMEs to expand across borders with confidence. Our core product system - TruBadge, ESR Score, Janu AI, and OneInbox - powers signal-driven decision-making for businesses worldwide. Incorporated in Singapore, Pepagora is at a Pre-Series A stage and scaling rapidly across international markets.

About the Role:

Own the engineering foundation for Pepagora's AI and Data Platform: ingestion, entity resolution, enrichment, evaluation, models, agents and knowledge-graph-enabled intelligence. The mandate includes an AI gateway, multiple named agents and production AI governance.

What You'll Be Doing:

- Design and own production AI/ML architecture

- Build RAG/agentic workflows grounded in trusted business data

- Create evaluation frameworks for quality, safety, latency and cost

- Build entity resolution, extraction, classification and enrichment systems

- Establish model/provider gateway patterns and observability

- Mentor AI researchers/interns and turn experiments into production capabilities

Who We're Looking For:

- Typically, 5+ years in software/data/ML with strong recent production AI ownership

- Strong software engineering plus applied ML/GenAI depth

- Production experience with LLM/RAG/agentic systems - not demos alone

- Strong Python and API/service engineering

- Understanding of evaluation, grounding, hallucination control, cost and latency trade-offs

- Ability to translate ambiguous business problems into measurable AI systems

Good to Have:

- Knowledge graphs/entity resolution

- Vector databases and retrieval systems

- MLOps/model serving

- Fine-tuning, embeddings or ranking models

- Experience with MCP/tool-using agents

Technology Environment:

Python - LLM APIs/open models - RAG - agents - vector search - evaluation - FastAPI - AWS - MLOps

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