Deploy, scale, and operate ML and Generative AI systems in cloud-based production environments (Azure preferred).
Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
Implement and operationalize agentic AI workflows with tool use, leveraging frameworks such as LangChain and LangGraph.
Develop reusable infrastructure and orchestration for GenAI systems using Model Context Protocol (MCP) and AI Development Kit (ADK).
Design and implement model and agent serving architectures, including APIs, batch inference, and real-time workflows.
Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
Integrate AI solutions into business workflows in collaboration with data engineering, application teams, and stakeholders.
Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
Ensure security, compliance, reliability, and cost optimization of AI services deployed at scale.

8 to 10 years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
Robust proficiency in Python, with experience building production-ready AI/ML services and workflows.
Proven experience deploying and supporting GenAI applications in real-world enterprise environments.
Experience with orchestration frameworks including but not limited to LangChain, LangGraph, and LangSmith.
Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems.
Experience working with cloud AI ecosystems (Azure AI, Azure ML, Databricks preferred).
Familiarity with containerization and deployment tools (Docker, Kubernetes, REST

Bachelors degree in computer science, Information Systems, Engineering, Computer Applications, or related field.

In addition to competitive salaries and benefits packages, Nisum India offers its employees some unique and fun extras:
Continuous Learning - Year-round training sessions are offered as part of skill enhancement certifications sponsored by the company on an as need basis. We support our team to excel in their field.
Parental Medical Insurance - Nisum believes our team is the heart of our business and we want to make sure to take care of the heart of theirs. We offer opt-in parental medical insurance in addition to our medical benefits.
Activities -From the Nisum Premier League's cricket tournaments to hosted Hack-a-thon, Nisum employees can participate in a variety of team building activities such as skits, dances performance in addition to festival celebrations.
Free Meals - Free snacks and dinner is provided on a daily basis, in addition to subsidized lunch.

Deploy, scale, and operate ML and Generative AI systems in cloud-based production environments (Azure preferred).
Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
Implement and operationalize agentic AI workflows with tool use, leveraging frameworks such as LangChain and LangGraph.
Develop reusable infrastructure and orchestration for GenAI systems using Model Context Protocol (MCP) and AI Development Kit (ADK).
Design and implement model and agent serving architectures, including APIs, batch inference, and real-time workflows.
Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
Integrate AI solutions into business workflows in collaboration with data engineering, application teams, and stakeholders.
Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
Ensure security, compliance, reliability, and cost optimization of AI services deployed at scale.

8 to 10 years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
Robust proficiency in Python, with experience building production-ready AI/ML services and workflows.
Proven experience deploying and supporting GenAI applications in real-world enterprise environments.
Experience with orchestration frameworks including but not limited to LangChain, LangGraph, and LangSmith.
Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems.
Experience working with cloud AI ecosystems (Azure AI, Azure ML, Databricks preferred).
Familiarity with containerization and deployment tools (Docker, Kubernetes, REST

Bachelors degree in computer science, Information Systems, Engineering, Computer Applications, or related field.

In addition to competitive salaries and benefits packages, Nisum India offers its employees some unique and fun extras:
Continuous Learning - Year-round training sessions are offered as p

Machine Learning/Gen Ai Engineer (Telangana)

Job Description & Responsibilities