Gen AI & ML Engineer

Nisum; Hyderabad, Pune District; On-site; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Competitive compensation

Certification sponsorship

Parental medical insurance

Employee engagement activities

Snacks & dinner provided

Cutting-edge AI at scale

Job summary

Nisum in Hyderabad, India is seeking an experienced Machine Learning Engineer / Generative AI Engineer to design, deploy and operate enterprise-scale AI solutions in cloud environments.

You will collaborate with cross-functional teams to build intelligent applications, implement AI workflows, and establish scalable AI platforms that deliver measurable business value, focusing on MLOps and production-grade systems.

Qualifications

• 8+ years of experience in ML engineering or AI platform engineering.
• Production-grade AI/ML applications and services experience in enterprise environments.
• Hands-on Generative AI and LLMs experience in enterprise settings.

Responsibilities

• Deploy and scale ML/Gen AI solutions in cloud environments (Azure preferred).
• Design and build retrieval augmented generation (RAG) apps with embeddings and vector databases.
• Develop AI workflows and tool integrations using LangChain / LangGraph.
• Create reusable AI infrastructure with MCP/ADK.
• Design model-serving architectures: REST APIs, batch and real-time inference.
• Establish observability, monitoring, governance, and cost optimization.

Skills

8 years experience

Python

Generative AI

LLM applications

MCP/ADK

RAG

LangChain

LangGraph

LangSmith

Azure AI / ML

Docker

Kubernetes

REST APIs

MLOps / LLMOps

Education

Bachelor's Degree in CS/Engineering/related

Tools

Databricks

Job description

We are seeking an experienced Machine Learning Engineer / Generative AI Engineer to join our growing AI team. In this role, you will be responsible for designing, deploying, and operating enterprise-scale AI and Generative AI solutions in cloud-based production environments. You will work closely with cross-functional teams to build intelligent applications, implement AI workflows, and establish scalable AI platforms that deliver measurable business value.

Key Responsibilities

• Deploy, scale, and manage Machine Learning and Generative AI solutions in cloud environments, with a preference for Azure-based ecosystems.
• Design and develop enterprise-grade Retrieval-Augmented Generation (RAG) applications using embeddings, vector databases, and retrieval pipelines.
• Build and operationalize Agentic AI workflows with tool integration using frameworks such as LangChain and LangGraph.
• Develop reusable AI infrastructure and orchestration frameworks using Model Context Protocol (MCP) and AI Development Kit (ADK).
• Design and implement model-serving architectures, including REST APIs, batch inference, and real-time AI services.
• Establish best practices for observability, monitoring, evaluation, governance, and performance optimization of AI systems.
• Collaborate with Data Engineering, Application Development, and Business teams to integrate AI solutions into enterprise workflows.
• Drive adoption of MLOps and LLMOps practices, including CI/CD automation, model versioning, testing, deployment, and lifecycle management.
• Ensure security, compliance, reliability, scalability, and cost optimization of AI services deployed in production environments.
• Contribute to architectural decisions and continuously improve AI platform capabilities.

Required Skills & Experience

• 8 years of experience in Machine Learning Engineering, AI Platform Engineering, MLOps, or related domains.
• Strong proficiency in Python and experience building production-grade AI/ML applications and services.
• Hands-on experience with Generative AI and Large Language Model (LLM) applications in enterprise environments.
• Experience in MCP (Model Context Protocol)/ADK (Agent Development Kit)
• Expertise in Retrieval-Augmented Generation (RAG), vector search, embeddings, and retrieval pipelines.
• Experience with orchestration frameworks such as LangChain, LangGraph, and LangSmith.
• Strong understanding of AI model serving, inference pipelines, monitoring, and observability.
• Experience with Azure AI, Azure Machine Learning, Databricks, or similar cloud AI platforms.
• Hands-on experience with Docker, Kubernetes, REST APIs, and cloud-native deployments.
• Knowledge of MLOps/LLMOps practices, including CI/CD, testing, version control, and deployment automation.
• Strong problem-solving skills and the ability to work in a collaborative, fast-paced environment.

Educational Qualification

• Bachelors Degree in Computer Science, Information Systems, Engineering, Computer Applications, or a related field.

Benefits

• Competitive compensation and benefits package.
• Continuous learning and certification sponsorship programs.
• Parental medical insurance coverage (optional enrollment).
• Employee engagement activities, hackathons, sports events, and cultural celebrations.
• Free snacks and dinner, along with subsidized lunch facilities.
• Opportunity to work on cutting-edge AI and Generative AI technologies at scale.