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Staff AI / DevOps Engineer [T500-20750] (Apply in 3 Minutes)

Staff AI / DevOps Engineer [T500-20750] (Apply in 3 Minutes)

ANSRBengaluru, Karnataka, India
18 hours ago
Job description

ANSR is hiring for one of its clients.

About Illumina :

Illumina is a leading developer, manufacturer, and marketer of life science tools and integrated systems dedicated to making genomics useful for all. Illumina’s integrated Indian global hub in Bengaluru, Illumina India Biotechnology Private Limited, is focused on technology activities that will help usher in the next wave of innovation in healthcare and medical research. If you’re eager to work on challenging projects that use cutting-edge technology to transform the future of healthcare, this is your chance to join a truly remarkable team.

Position Summary :

This role is for a Staff AI / DevOps Engineer based in Bangalore, India, who will be a key member of the Infrastructure and Cloud Services. Your primary focus will be on designing, building, and deploying automated, AI-powered bot solutions to serve various functions across the department.

In this role, you’ll harness your expertise to build infrastructure which enables your team and the org to manage autonomous agents, machine learning systems and other applications in the AI domain. You’ll design and manage federated AI ecosystems, including MCP servers, agents and enterprise AI tooling, while orchestrating agent deployment across distributed systems. This role demands technical depth, strong communication, and a passion for building transformative enterprise AI infrastructure.

You will be a subject matter expert in bridging the gap between infrastructure operations and AI / ML, leveraging Generative AI and Large Language Models (LLMs) to create intelligent, self-service solutions. The ideal candidate has a strong background in DevOps, cloud engineering, and a passion for applying AI to solve real-world operational challenges.

Responsibilities :

  • Design and implement AI infrastructure to support federated agent development and distributed deployment across the organization to streamline common infrastructure and cloud service requests and support tasks.
  • Manage and orchestrate AI agents to generate architecturally sound code, ensuring adherence to enterprise standards and best practices.
  • Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise integration.
  • Accelerate code review processes by leveraging AI agents for automated analysis, quality checks, and architectural validation.
  • Integrate AI models and APIs, including LLMs and generative AI, into the bot solutions to provide natural language understanding and intelligent responses.
  • Develop and manage infrastructure-as-code (IaC) using tools like Terraform or Ansible to provision and configure resources on AWS, Azure.
  • Establish robust monitoring, governance, and security frameworks for AI agent operations in enterprise environments.
  • Implement and manage secure authentication and authorization systems for MCP servers, including OAuth flows and API security.
  • Collaborate closely with product owners and internal customers to gather requirements and deliver solutions that improve efficiency and user experience.
  • Act as a forward deployed engineer, working with different functional teams across the Infrastructure & Cloud Services department to coach on AI infrastructure best practices and guide adoption.
  • Provide technical leadership in transitioning traditional development practices to AI-augmented approaches
  • Mentor and guide junior engineers, promoting best practices in software development, AI integration, DevOps, Cloud and Platform Engineering.

Qualifications :

  • Typically requires a minimum of 8 years of professional software development experience with a demonstrated ability to architect and build scalable systems with a bachelor's degree; or 6 years with a master's degree; or equivalent experience.
  • Experience with AI / ML infrastructure, agent orchestration, or similar AI-powered development tools.
  • Proficiency in Python, TypeScript / JavaScript, and experience with AI / ML frameworks and libraries.
  • Strong understanding of enterprise software architecture patterns and distributed systems design.
  • Experience with cloud platforms (AWS, Azure) and infrastructure-as-code tools.
  • Experience with Docker, Kubernetes, and container orchestration in production environments.
  • Strong understanding of information security principles, OAuth 2.0 / OpenID Connect flows, API security, and secure system design.
  • Strong communication and mentoring skills with the ability to collaborate across different teams.
  • Basic understanding of enterprise services like Microsoft 365 and IAM (Identity and Access Management) and their APIs (e.g., Microsoft Graph API, Azure AD).
  • Excellent problem-solving skills and the ability to work in an innovative, fast-paced incubator environment.
  • Preferred Qualifications :

  • Demonstrated experience in a product or solutions-oriented role, creating tools for internal customers.
  • Relevant certifications from AWS, Azure, or professional certifications in AI / ML are highly desirable.
  • Knowledge of AWS services such as Agent Core, Bedrock, and Lambda, or similar services on Azure including AI Foundry, Agent Loop, and Azure Functions is a significant plus.
  • Knowledge of MCPs / APIs and integration patterns for common enterprise tools like ServiceNow, Jira, Confluence, GitHub, etc., is a plus.
  • Experience with AI agent frameworks, LLM integration, or Model Context Protocol (MCP) implementations.
  • Background in building federated systems or multi-agent AI platforms.
  • Experience with AI governance, security, and compliance in enterprise environments.
  • Familiarity with code generation tools, automated testing frameworks, and AI-powered development workflows.
  • Knowledge of vector databases, embedding systems, and retrieval-augmented generation (RAG) architectures.
  • Previous experience managing transitions from traditional to AI-augmented development practices.
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