Company Name

GENPACT ( Ahmedabad )

Job Description

• Job Description:
  • Inviting applications for the role of Lead Consultant - MLOps Engineer!
  • In this role, you will define, implement and oversee the MLOps strategy for scalable, compliant, and cost-efficient deployment of AI/GenAI models across the enterprise. This role combines deep DevOps knowledge, infrastructure architecture, and AI platform design to guide how teams build and ship ML models securely and reliably.
  • You will establish governance, reuse, and automation frameworks for AI infrastructure, including Terraform-first cloud automation, multi-environment CI/CD, and observability pipelines.
  Responsibilities:
  • Architect secure, reusable, modular IaC frameworks across cloud and regions for MLOps
  • Lead the development of CI/CD pipelines and standardize deployment frameworks.
  • Design observability and monitoring systems for ML/GenAI workloads.
  • Collaborate with platform, data science, compliance and Enterprise Architecture teams to ensure scalable ML operations.
  • Define enterprise-wide MLOps architecture and standards (build deploy monitor)
  • Lead design of GenAI/LLMOps platform (Bedrock/OpenAI/Hugging Face + RAG stack)
  • Integrate governance controls (approvals, drift detection, rollback strategies)
  • Define model metadata standards, monitoring SLAs, and re-training workflows
  • Influence tooling, hiring, and roadmap decisions for AI/ML delivery
  • Be engaging in the design, development and maintenance of data pipelines for various AI use cases
  • Required to actively contribution to key deliverables as part of an agile development team
  • Qualifications we seek in you!
  Minimum Qualifications:
  • Good years of experience in DevOps or MLOps roles.
  • Degree/qualification in Computer Science or a related field, or equivalent work experience
  • Strong Python programming skills.
  • Hands on experience in containerised deployment.
  • Proficient with AWS (SageMaker, Lambda, ECR), Terraform, and Python.
  • Demonstrated experience deploying multiple GenAI systems into production.
  • Hands-on experience deploying 3-4 ML/GenAI models in AWS.
  • Deep understanding of ML model lifecycle: train test deploy monitor retrain.
  • Experience in developing, testing, and deploying data pipelines using public cloud.
  • Clear and effective communication skills to interact with team members, stakeholders and end users
  • Knowledge of governance and compliance policies, standards, and procedures
  • Exposure to RAG/LLM workloads and model deployment infrastructure.
  • Experience in developing, testing, and deploying data pipelines
  • Preferred Qualifications/ Skills
  • Experience designing model governance frameworks and CI/CD pipelines.
  • Knowledge of governance and compliance policies, standards, and procedures
  • Advanced understanding of platform security, cost optimization, and ML observability.

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