Artificial Intelligence Engineer

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

Were hiring an AI Engineer who can design, build, and ship productiongrade RetrievalAugmented Generation (RAG) systems and AI Agents endtoend. You will work across the stack Python for data/ML services and MERN (MongoDB, Express.js, React, Node.js) for the product surfaceto 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.

Youre handson with vector databases, LLM orchestration, evaluation, and monitoring. You write clean APIs, ship thoughtful UIs, and automate deployment with CI/CD.

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

• 23 years software engineering (or equivalent depth), with production experience in both:
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• Python (APIs, data/ML services, packaging, testing with Pytest)
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• MERN : MongoDB, Express.js, React, Node.js (TypeScript preferred)
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• RAG & Agents shipped to production: retrieval pipelines, embeddings, hybrid search, reranking, function/tool calling, and multistep workflows.
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• Vector databases : one or more of Pinecone, Weaviate, Qdrant, Milvus, pgvector schema design, index tuning, and ops.
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• MCP servers : built/maintained Model Context Protocol servers or equivalent agenttool bridges; experience defining tools, auth, isolation, and telemetry.
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• Cloud & DevOps : Docker, Kubernetes or serverless (Cloud Run/Lambda), CI/CD (GitHub Actions/GitLab), infrastructure as code (Terraform/Pulumi).
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• Testing & quality : unit/integration tests, load testing, contract tests for tool/agent interfaces, data quality checks for corpora.
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• Security mindset : data governance, secrets management, least privilege, dependency hygiene.

• Backend: Python (FastAPI), Node.js/TypeScript (Express/Nest)
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• Frontend: React (Vite/Next.js), WebSockets/ServerSent Events
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• Data/RAG: MongoDB, Postgres, S3/GCS; vector DBs (Pinecone/Weaviate/Qdrant/Milvus/pgvector)
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• Agents/Orchestration: LangChain/LangGraph, semantickernel, custom state machines; MCP servers & tools
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• Infra: Docker, Kubernetes/Cloud Run, Terraform, GitHub Actions; Redis for cache/queues
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• Observability & Eval: OpenTelemetry, Langfuse, RAGAS/TruLens/DeepEval, Prometheus/Grafana

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