Employer Active
Job Alert
You will be updated with latest job alerts via emailJob Alert
You will be updated with latest job alerts via emailPosition 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 youll 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. Youll 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 bachelors degree; or 6 years with a masters 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.
Required Experience:
Staff IC
Full-Time