AI Engineer

Hiring: AI / MLOps Engineer (LLMs, RAG, Agentic AI)

Location: Noida/Gurugram, Hyderabad | Type: Full-time

Experience : 1-4 years

Build AI systems that actually ship to production.

At Simplify VMS, were not experimenting in notebookswere deploying real, production-grade AI systems that power modern hiring and workforce solutions at scale.

If you love taking LLMs from prototype production, enjoy working with agentic AI, RAG pipelines, and scalable infrastructure, and want real ownership, this role is for you.

Why this role is exciting

• Work on production LLM & agentic AI systems
• Build chatbots, copilots, and autonomous agents used in real hiring and VMS workflows
• Own the end-to-end MLOps lifecycle deploy, monitor, optimize, repeat
• Collaborate closely with senior AI leadership
• Remote-first, high-impact, zero bureaucracy

What youll work on

• Designing and deploying LLM & RAG systems at production scale
• Productionizing LLM workflows using hosted APIs or open-source models
• Building inference pipelines using vLLM, TGI, or similar frameworks
• Creating agentic workflows using LangChain / LangGraph
• Setting up CI/CD pipelines for models, prompts, and retrieval configurations
• Deploying services with Docker & Kubernetes
• Designing LLM evaluation frameworks (quality, hallucination detection, regression)
• Implementing monitoring & observability (latency, cost, token usage, retrieval quality)
• Building backend APIs using Python + FastAPI

What were looking for

• 1-4 years in Software Engineering / ML Engineering / MLOps
• Candidates from Tier1/Tier2 Engg grads
• Strong Python skills + experience building production APIs
• Hands-on experience with LLMs (OpenAI or open-source models)
• Practical exposure to LangChain / LangGraph
• Solid understanding of RAG, embeddings, vector databases
• Experience with Docker (Kubernetes is highly desirable)
• Cloud experience (AWS preferred)
• Experience with leveraging tools like Cursor and Opus for coding

Nice to have (but not required)

• Model serving tools like vLLM, Ray Serve, MLflow
• LLM performance optimization (quantization, throughput tuning)
• Experience with vector DBs such as Pinecone, Milvus, FAISS, Weaviate, Qdrant
• LLM evaluation & safety frameworks
• Document processing pipelines (PDFs, OCR, unstructured data ingestion)
• Agent-based enterprise workflows

Why Simplify VMS

• AI-first product organization building scalable workforce and hiring automation systems
• High ownership, high trust, high impact
• Opportunity to shape the companys LLM & MLOps foundation

Interested ? DM me or mail me your CVs @ shashi.prakash@thehirehq.com