Senior AI Engineer

Maruti Suzuki India Ltd.; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Maruti Suzuki India Ltd. in Gurugram seeks a Senior AI Engineer to design, build, and deploy enterprise-grade Generative AI and Agentic AI solutions across cloud and on-premise environments.

You will own end-to-end delivery from PoC to production, collaborating with automotive domain experts and business stakeholders. You will work on RAG/GraphRAG, multi-agent architectures, and ensure scalable, cloud-agnostic deployments on Azure, AWS, GCP, and on-premise platforms using contemporary tools and

Qualifications

• 5+ years of software engineering or AI/ML experience with GenAI and enterprise-grade solutions.
• Hands-on experience with LangGraph, AutoGen, Semantic Kernel or similar frameworks.
• Experience deploying AI/GenAI solutions on Azure, AWS, GCP and on-premise.
• Strong Python, FastAPI and Flask proficiency for production systems.

Responsibilities

• Develop enterprise GenAI and Agentic AI solutions for complex business use cases.
• Collaborate with stakeholders to translate requirements into scalable AI products.
• Work with automotive domain experts to derive domain insights for AI apps.
• Design and build RAG, GraphRAG, and multi-agent applications.
• Architect cloud-agnostic AI solutions across Azure, AWS, GCP and on-premise.
• Host AI applications on-premise using vLLM, Ollama or similar platforms.
• Own lifecycle from PoC and MVP to production deployment and optimization.
• Evaluate agents and track actions, tool calls, execution flows, latency and cost.
• Fine-tune open-source models for domain-specific use cases.

Skills

Python

FastAPI

Flask

Azure

AWS

GCP

LangGraph

AutoGen

Semantic Kernel

GPU CUDA

Job description

We are seeking a Senior AI Engineer to design, build, and deploy enterprise-grade Generative AI and Agentic AI solutions. The role requires strong hands-on engineering, architecture, stakeholder collaboration, and end-to-end ownership from PoC to production across cloud and on-premise environments.

Key Responsibilities

• Develop innovative Enterprise GenAI and Agentic AI solutions for complex business use cases.
• Collaborate with business stakeholders to understand requirements and translate them into meaningful, scalable solutions.
• Work with automotive domain experts to gain relevant insights and incorporate them into AI applications.
• Design and build enterprise-grade RAG, GraphRAG, and multi-agent applications.
• Architect cloud-agnostic AI/GenAI solutions across Azure, AWS, GCP, and on-premise environments.
• Build and host AI applications and models on-premise using vLLM, Ollama, or similar platforms.
• Own the complete application lifecycle, from PoC and MVP to production deployment and ongoing optimization.
• Evaluate agents and implement efficient tracking of agent actions, tool calls, execution flows, quality, latency, cost, and failures.
• Fine-tune and optimize open-source SLMs/LLMs for domain-specific use cases.

Required Skills

• Hands-on experience building agents with LangGraph, AutoGen, Semantic Kernel, Google ADK, Microsoft Agent Framework, or similar frameworks.
• Experience building agents on Microsoft Copilot Studio, AWS Bedrock AgentCore, Azure AI Foundry, or comparable platforms.
• Strong expertise in Python, with mandatory experience in FastAPI and Flask.
• Experience developing and deploying enterprise applications on Azure, AWS, and/or GCP.
• Experience architecting and delivering cloud-agnostic AI/GenAI solutions.
• Experience hosting and operating models and applications in on-premise environments.
• Experience with domain fine-tuning of open-source models such as Gemma, Llama, and Mistral.
• Experience building production-grade RAG and GraphRAG applications.
• Experience with agent evaluation, observability, benchmarking, tracing, and AgentOps practices.
• Knowledge of Transformers, GANs, Vision-Language Models (VLMs), multimodal AI, SLMs, and LLMs.
• Familiarity with machine learning algorithms, including classification, regression, and clustering.
• Ability to work effectively in a fast-paced environment and take end-to-end ownership.

Must to Have

• Knowledge of GPUs and CUDA, including efficient GPU utilization for model hosting, inference, and fine-tuning.
• Familiarity with LoRA, QLoRA, PEFT, and other parameter-efficient fine-tuning techniques.
• Hands-on experience building agents with LangGraph, AutoGen, Semantic Kernel, Microsoft Agent Framework, or similar frameworks.
• Experience with Docker, Kubernetes, CI/CD, MLOps, and LLMOps.
• Experience with SQL and NoSQL databases.

Experience

5+ years of overall software engineering or AI/ML experience, with strong hands-on exposure to Generative AI, Agentic AI, and production-grade AI solutions.