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

2–3 years

software engineering (or equivalent depth), with

production

experience in both: Python

(APIs, data/ML services, packaging, testing with Pytest) MERN

: MongoDB, Express.js, React, Node.js (TypeScript preferred) RAG & Agents

shipped to production: retrieval pipelines, embeddings, hybrid search, reranking, function/tool calling, and multi‑step workflows. Vector databases

: one or more of

Pinecone, Weaviate, Qdrant, Milvus, pgvector

—schema design, index tuning, and ops. MCP servers

: built/maintained

Model Context Protocol

servers or equivalent agent‑tool bridges; experience defining tools, auth, isolation, and telemetry. Cloud & DevOps

: Docker, Kubernetes or serverless (Cloud Run/Lambda), CI/CD (GitHub Actions/GitLab), infrastructure as code (Terraform/Pulumi). Testing & quality

: unit/integration tests, load testing, contract tests for tool/agent interfaces, data quality checks for corpora. Security mindset

: data governance, secrets management, least privilege, dependency hygiene.

Tech Stack You’ll Touch

Backend:

Python (FastAPI), Node.js/TypeScript (Express/Nest) Frontend:

React (Vite/Next.js), WebSockets/Server‑Sent Events Data/RAG:

MongoDB, Postgres, S3/GCS; vector DBs (Pinecone/Weaviate/Qdrant/Milvus/pgvector) Agents/Orchestration:

LangChain/LangGraph, semantic‑kernel, custom state machines; MCP servers & tools Infra:

Docker, Kubernetes/Cloud Run, Terraform, GitHub Actions; Redis for cache/queues Observability & Eval:

OpenTelemetry, Langfuse, RAGAS/TruLens/DeepEval, Prometheus/Grafana Are you one of us?

Mail your resume at ag@saakh.in

Visit us: Website –