Senior AI Engineer
Senior AI Engineer
Location: Gurgaon, India
Work Model: Hybrid
Experience: 10–15 Years
Employment Type: Permanent
Role Type: Individual Contributor (IC)
Note : Master’s degree (MS/M.Tech/ME or equivalent) from a reputed institute is mandatory.
Role Overview
We are looking for an experienced Senior AI Engineer to design, develop, and deploy advanced AI solutions across enterprise platforms. The ideal candidate will bring strong foundations in Machine Learning and Artificial Intelligence, combined with hands-on expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI and multimodal AI systems.
This is a senior individual contributor role requiring deep technical expertise, strong engineering fundamentals, and the ability to take AI solutions from experimentation to production at enterprise scale.
Key Responsibilities
- Design, develop, and deploy production-grade AI and Machine Learning solutions.
- Build advanced Generative AI applications using LLMs, RAG architectures and agentic AI frameworks.
- Design and implement multi-agent systems, tool-calling workflows and Model Context Protocol (MCP) integrations.
- Develop multimodal AI solutions involving text, images, documents and other data modalities.
- Optimize model inference, latency, throughput, scalability and resource utilization.
- Build scalable model-serving infrastructure using tools such as vLLM, NVIDIA Triton or Hugging Face TGI.
- Work with GPU-accelerated environments and distributed AI workloads.
- Implement evaluation, monitoring, experimentation and continuous improvement of AI models.
- Collaborate with engineering, architecture and product teams to translate business requirements into scalable AI solutions.
- Drive technical excellence in AI engineering, coding standards, architecture and production deployment.
Required Technical Skills
AI & Machine Learning
- Strong fundamentals in Artificial Intelligence, Machine Learning and Deep Learning.
- Hands-on experience developing and deploying production AI/ML models.
- Strong understanding of neural networks, model training, fine-tuning and inference.Generative AI & LLMs
- Hands-on experience with LLMs and Generative AI applications.
- Strong expertise in RAG architecture, embeddings, vector databases and semantic search.
- Experience building agentic AI applications and multi-agent orchestration.
- Knowledge of MCP (Model Context Protocol), tool calling and AI workflow orchestration.
- Experience with multimodal AI systems is highly desirable.Frameworks & Engineering
- Strong Python programming skills.
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex or AutoGen.
- Experience with PyTorch and/or TensorFlow.
- Understanding of APIs, asynchronous programming, concurrency and distributed systems.Model Deployment & Infrastructure
- Experience with model serving and inference optimization.
- Familiarity with vLLM, NVIDIA Triton, Hugging Face TGI or equivalent technologies.
- Hands-on exposure to Kubernetes, Docker and cloud-native deployment.
- Experience working with GPU infrastructure, preferably NVIDIA A100/H100 environments.
- Familiarity with MLflow, Weights & Biases or equivalent MLOps platforms.
Education & Experience
- 10–15 years of overall experience in software engineering, AI/ML engineering or related technology domains.
- At least 5 years of hands-on experience in Machine Learning or production AI engineering.
- Strong recent experience in Generative AI, LLMs, RAG and agentic AI systems.
- Demonstrated experience taking AI solutions from proof of concept to production deployment.
- Master’s degree (MS/M.Tech/ME or equivalent) from a reputed institute is mandatory.
- Candidates from premier engineering and research institutions will be prioritized.
- PhD in AI, Machine Learning, Computer Science or a related discipline is an advantage.
What We Are Looking For
- A hands-on AI engineering specialist with strong technical depth.
- Someone who can architect and build production-grade AI systems independently.
- Strong problem-solving, analytical and engineering capabilities.
- Ability to work across complex enterprise technology environments.
- A strong individual contributor who remains actively involved in design, coding, experimentation and deployment.
Note: This is a pure Individual Contributor position and does not involve people-management responsibilities.