Principal Engineer - Agentic Engineering

About the Opportunity Job Type: Permanent Application Deadline: 31 August 2026 Job Description             Title                 Principal Engineer II Department       CSP Location          Bengaluru Reports To       Head of Platform Design and Solutions Level                6 We share a commitment to making things better for clients and each other. We continually explore new technology and different ways of working to put our clients first. So, bring your boldest ideas to our (name of team/business area) team and feel like you are making progress. About your team You will join the CSP platform and design function operating across multiple squads and domains. The team drives technical excellence and consistency for agentic AI and MLOps capabilities, ensuring solutions are secure, scalable, reliable, and aligned to enterprise standards. We work in close partnership with Product, Architecture, Data Engineering, Security, and Platform teams. Role summary Act as technical authority across squads, driving consistent engineering practices, architecture alignment, and engineering standards for agentic AI and ML-enabled services. Own the technical delivery of CSP's agent interoperability capability, including shared APIs, Model Context Protocol (MCP) servers, reusable agents, and agent-to-agent interaction patterns. Own technical direction and solve complex cross-team challenges across CSP platforms. Partner with Engineering Managers, Architects, and Product to shape scalable solutions and influence roadmaps. Ensure alignment with enterprise standards, security controls, and regulatory requirements. Champion engineering excellence by mentoring senior engineers, promoting reusability and automation, and supporting responsible AI adoption.

Technical outcomes Drive technical alignment and architecture consistency across squads. Deliver reusable APIs, MCP servers, and controls for secure agent-to-agent and tool interaction across CSP. Ensure cross-team technical risks are identified, tracked, and mitigated. Support resolution of major production issues and escalations for AI and ML services. Technical contribution Define technical direction and enforce engineering standards for agentic AI and MLOps. Lead complex design decisions and cross-team integrations across data, model, and platform layers. Design, build, and operate production-grade APIs, MCP servers, agent services, and tool integrations used across CSP. Define reusable agent interaction and orchestration patterns, covering contracts, versioning, resilience, tracing, security, and auditability. Build and improve CI/CD pipelines for ML and agentic workflows, including versioning and rollback controls. Promote reusability, scalability, and modernisation across solutions. Contribute to enterprise standards and engineering communities, including Inner Source practices. Mentor senior engineers and build technical capability across teams. Define and enforce non-functional requirements across squads, including reliability, resilience, security, and observability. Ensure future readiness through technology evaluation and modernisation planning. Stakeholder management Partner with Product, Architecture, and business stakeholders. Influence roadmap and investment decisions using technical evidence and risk-aware options. AI adoption Promote adoption of AI-assisted engineering and agentic delivery patterns at scale. Define guardrails, evaluation, and release controls for secure, reliable, and responsible AI usage. Cost discipline Drive cost-efficient architecture and infrastructure decisions across squads. Evaluate build versus buy trade-offs for cross-team solutions. Ensure licensing, model serving, and cloud costs are optimized across the domain. Success indicators Consistent engineering practices and adopted, reliable shared APIs, MCP servers, and agent interaction patterns across CSP. Reduced technical debt