COCoditudeVerified listing
Senior AI Engineer, Knowledge Graph & GenAI
PuneOn-siteSenior
Good timing - competition is buildingPosted 5d ago
Applicants who checked fit first are 3.1× more likely to hear back
Before you apply
The post's words + ASAI's dataOn-site in Pune.
OK with that?5+ years asked. Machine Learning Engineer roles in Pune usually ask 4-7; two thirds ask 5+.
You have them?No pay range in the post.
Not a repost. 1 of Coditude's last 28 posts was a repost; all 7 of its open roles are here.
48 Machine Learning Engineer roles posted in Pune this week, 355 open. See them →
Skills listed in the post · tap the ones you have · 0 of 8
+38 more
You almost certainly match several of these already.
This post sets 2 stated bars and lists 8 skills. Tap where you stand - nothing is saved, no account needed.
ASAI checks this on every job for you, automatically, so you apply where you fit.
Fit Breakdown
ExampleSTRONGMATCH
Skills alignmentPartial
Experience fitPerfect
How an ASAI match score looks. Yours is built from your resume, not a guess.
Your score for this role already exists - sign in to view it
ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.
Always free · no credit card · 1 tap with Google
Tools on this job
60-Day PassStarts free · 60-Day Pass ₹149 for 60 days, GST included
Free account, no card needed.
The job post
557 words · from Coditude's careers siteROLE OVERVIEW
We are looking for a hands-on Senior AI Engineer to build production-grade AI systems using Generative AI, RAG, GraphRAG, knowledge graphs, vector search, LLM orchestration and computer vision. You will work on real-world AI products across healthcare, enterprise software and data platforms, taking solutions from experimentation to production.
The ideal candidate has strong software engineering fundamentals, hands-on experience with LLMs and RAG systems, and the ability to work across AI, backend, data and cloud technologies.
KEY RESPONSIBILITIES
AI & GenAI Engineering
- Build production-grade RAG and GraphRAG systems combining LLMs, vector search, knowledge graphs and structured data.
- Develop LLM workflows using LangChain, LangGraph, LlamaIndex or equivalent frameworks.
- Build AI agents, tool-calling workflows and stateful AI pipelines.
- Implement embeddings, semantic search, chunking, reranking and hybrid retrieval.
- Develop text-to-SQL, text-to-Cypher and natural-language query systems.
- Build LLM evaluation pipelines and optimise accuracy, latency and cost.
- Work with LLM APIs and batch processing using models such as OpenAI, Anthropic and other foundation models.
Knowledge Graphs & Data
- Design and work with Neo4j knowledge graphs, including graph modelling and Cypher queries.
- Build semantic enrichment pipelines including entity extraction, entity linking and relationship extraction.
- Develop data pipelines using Apache Airflow or equivalent orchestration tools.
- Work with PostgreSQL, Redis, Qdrant and other vector databases.
- Process and index large-scale enterprise datasets for AI applications
Platform & Data Engineering
- Architect multi-tenant SaaS platforms with strong data isolation across database, storage, API and orchestration layers.
- Build and maintain data pipelines with Apache Airflow, including ETL, DAG orchestration, data quality checks and real-time synchronisation.
- Design scalable APIs and services in Python (FastAPI) and Node.js / TypeScript, backed by PostgreSQL, Neo4j, Redis and vector stores.
- Deploy and operate workloads on AWS and GCP using serverless, containerised and event-driven patterns.
Security & Compliance
- Enforce HIPAA-grade controls: encryption with KMS, RBAC, JWT/OAuth authentication, audit logging and per-tenant key management.
- Translate regulatory and client compliance requirements into concrete architecture and engineering standards.
Leadership & Delivery (Nice to Have)
- Lead and mentor a team of 2 to 4 engineers through architecture reviews, code reviews, sprint planning and delivery milestones.
- Act as the primary technical point of contact for clients: gather requirements, propose solutions, report progress and manage expectations.
- Raise the bar on code quality, documentation, testing and engineering practices across the team.
REQUIRED SKILLS & EXPERIENCE
- 5+ years of software engineering experience with significant hands-on experience in AI/ML or GenAI.
- Strong Python skills and experience with FastAPI.
- Hands-on experience building RAG, LLM and AI agent applications.
- Experience with LangChain, LangGraph, LlamaIndex or equivalent.
- Strong understanding of embeddings, vector search and semantic retrieval.
- Experience with Qdrant, Pinecone, ChromaDB, pgvector or similar.
- Experience with Neo4j and Cypher is highly desirable.
- Strong PostgreSQL / SQL skills and experience with Redis.
- Experience with Node.js / TypeScript; Next.js / React is a plus.
- Experience with AWS and/or GCP, Docker and CI/CD.
- Strong understanding of APIs, asynchronous processing, testing and debugging.
- Good communication skills and ability to independently own technical problems.
GOOD TO HAVE
- Experience with LLM or vision model fine-tuning workflows, GPU-backed training and model registries.
- Computer vision with PyTorch / TensorFlow, OpenCV, YOLO or U-Net.
- Payment and real-time integrations such as Stripe, Razorpay, Socket.io or Pusher.
- Comfort with AI-assisted development tools such as Cursor or Claude Code.
QUALIFICATIONS
- Bachelor’s degree in Engineering (IT / Computer Science) or equivalent practical experience.
Free · no signup
Get tomorrow's jobs before you have to search
