Artificial Intelligence Engineer

(RAG & Agent Systems) — MERN + Python

Experience Required : 2-3 years

Location : Work from office : Ahmedabad

Salary range – Upto Rs 100k per month.

Positions : 01

About us :

Saakh is an AI First B2B Fintech startup enabling SMEs with business intelligence.

1) Take data driven lending decisions

2) Automate payment collections

3) Prevent late payments

4) Delegate recoveries of stuck payments

5) Build Digital Reputation Identity of businesses

About the Role

We’re hiring an AI Engineer who can design, build, and ship production‑grade Retrieval‑Augmented Generation (RAG) systems and AI Agents end‑to‑end. You will work across the stack— Python for data / ML services and MERN (MongoDB, Express.js, React, Node.js) for the product surface—to deliver secure, observable, and scalable intelligent features. A key part of the role is building and operating MCP servers (Model Context Protocol) and tooling connectors that expose internal data and actions safely to agents.

You’re hands‑on with vector databases, LLM orchestration, evaluation, and monitoring. You write clean APIs, ship thoughtful UIs, and automate deployment with CI / CD.

What You’ll Do

• Design & implement RAG pipelines : ingestion / ETL, chunking & metadata, embeddings, hybrid search (keyword + vector), reranking, context caching, freshness & re‑indexing.
• Build multi‑step AI agents : tool‑use, function calling, planning / state machines (e.g., LangGraph / semantic‑kernel / AutoGen equivalents), error recovery, memory design.
• Develop MCP servers & connectors : define tools / schemas, auth, rate‑limits, multi‑tenant isolation, and logging to safely expose internal systems to agents.
• Own MERN product surfaces : React frontends (chat / task UIs), Node / Express APIs, WebSockets / Streaming for token‑level updates, and MongoDB persistence.
• Engineer Python microservices : retrieval, orchestration, evaluation, and batch jobs; package as containers; expose fast, typed APIs.
• Vector DB operations : design indexes, choose distance metrics / ANN algorithms (e.g., HNSW / IVF), tune recall / latency; manage Pinecone / Weaviate / Qdrant / Milvus / pgvector.
• LLMOps, evaluation & observability : establish offline / online evals (RAGAS / TruLens / DeepEval), guardrails, tracing (OpenTelemetry / Langfuse), metrics, and A / B tests.
• Security & governance : prompt‑injection defenses, PII redaction, data scoping / RBAC, audit logs, rate limiting, content filters, policy‑as‑code.
• Performance & cost : caching, batching, streaming, model selection, autoscaling, token / latency budgets, and cost attribution.
• Work cross‑functionally with Product, Data, and Infra to prioritize use cases and ship reliable, testable features on a predictable cadence.

Required Qualifications

Tech Stack You’ll Touch

Are you one of us?

Mail your resume at ag@saakh.in

Visit us :

Website – Https : / / www.saakh.in