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, we’re not experimenting in notebooks—we’re 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 you’ll 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 we’re 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 company’s LLM & MLOps foundation

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