Senior AIML Engineer

Nisum; Khordha, Hyderabad; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Nisum is seeking an experienced Machine Learning Engineer / Generative AI Engineer in India 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.

The role emphasizes RAG development, embedding use-cases, and production-grade ML services, with Kubernetes, Docker, and CI/CD practices.

Qualifications

• 5-12 years of experience in ML/AI engineering or related roles.
• Strong Python and production-grade AI/ML development skills.
• Hands-on Generative AI and LLM applications in enterprise settings.
• Expertise in RAG, embeddings, vector databases, and retrieval pipelines.
• Experience with LangChain, LangGraph, and LangSmith.
• Knowledge of AI model serving, inference pipelines, and observability.
• Experience with Azure AI/Azure ML and cloud platforms.
• Hands-on Docker, Kubernetes, REST APIs, and cloud-native deployments.
• Familiarity with CI/CD, MLOps, and deployment automation.
• Able to collaborate across data, app development, and business teams.

Responsibilities

• Deploy, scale, and manage ML/GenAI solutions in cloud environments.
• Design and develop enterprise-grade RAG apps using embeddings and vector databases.
• Build agentic AI workflows with LangChain/LangGraph and tool integrations.
• Develop reusable AI infrastructure with MCP and ADK.
• Design model-serving architectures (REST, batch, real-time).
• Establish observability, governance, and performance optimization practices.
• Collaborate with data engineering, app dev, and business teams to integrate AI.
• Drive MLOps/LLMOps adoption, CI/CD, versioning, testing, deployment.
• Ensure security, reliability, cost optimization in production.
• Contribute to architectural decisions and platform evolution.

Skills

Python

Production AI

Generative AI

LLM apps

RAG

Vector search

Embeddings

Retrieval pipelines

LangChain

LangGraph

LangSmith

Model serving

Inference pipelines

Observability

Azure AI

Azure ML

Databricks

Docker

Kubernetes

REST APIs

CI/CD

MLOps

LLMOps

Education

Bachelor's Degree in CS/Engineering/IS/CA

Tools

Docker

Kubernetes

Azure ML

LangChain

LangGraph

LangSmith

Databricks

Job description

Machine Learning Engineer / Generative AI Engineer

Experience: 512 Years
Location: India
Employment Type: Full-Time

About the Role

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

• 5-12 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.
• 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

• Bachelor's Degree in Computer Science, Information Systems, Engineering, Computer Applications, or a related field.