Job Summary

Consulting Senior Manager, AI Agentic Platform Engineering (Backend / Python):

We are looking for a Senior Manager for the EY.ai Center for Reimagination who can lead backend and AI agentic platform engineering across complex enterprise transformation programmes. The role will own technical direction, delivery governance and capability scaling for Python-led backend platforms and production-grade agentic solutions, leveraging frameworks such as Microsoft Agent Framework, LangGraph, OpenAI Agents SDK, Semantic Kernel, AutoGen, CrewAI or equivalent orchestration patterns to deliver secure, scalable and commercial client outcomes.

The successful candidate will operate at the intersection of architecture, programme delivery, people leadership and stakeholder management. This role requires the ability to shape platform strategy, lead managers and senior engineers, influence client and internal leadership, and establish reusable engineering practices that can be scaled across programmes.

Your Key Responsibilities

- Own the backend platform engineering strategy across multiple workstreams, teams or programmes, with explicit alignment to business objectives and client outcomes.
- Define and govern architecture principles for Python-led backend platforms, Go services, API ecosystems, integration layers, data movement and cloud-native deployment models.
- Lead technical governance forums, architecture reviews, release readiness checkpoints, dependency management and risk review mechanisms.
- Partner with senior stakeholders, programme leaders, product owners and architects to convert strategic priorities into executable engineering roadmaps.
- Build and scale high-performing engineering teams by defining role clarity, capability needs, staffing plans, mentoring models and quality expectations.
- Drive consistent engineering standards across secure coding, automated testing, CI/CD, observability, documentation,



operational resilience and production support readiness.
- Identify platform investment areas, reusable assets, accelerators and automation opportunities that improve delivery velocity and reduce programme risk.
- Manage technical escalations, unblock cross-team dependencies and ensure complex delivery issues are resolved with clear ownership and decision-making.
- Guide managers, architects and senior developers through design trade-offs, delivery planning, quality gates and stakeholder communication.
- Promote AI-assisted engineering, agentic application architecture and agent-led delivery practices where they improve productivity, code quality, testing coverage, engineering knowledge reuse and enterprise automation outcomes.
- Define reference architectures for agentic applications using frameworks such as Microsoft Agent Framework, LangGraph, OpenAI Agents SDK, Semantic Kernel, AutoGen, CrewAI or similar orchestration patterns, including tool calling, memory, guardrails, human-in-the-loop workflows, observability and enterprise integration.
- Lead the design and delivery of agentic workflow patterns that combine reasoning, planning, tool execution, retrieval, memory and business-rule orchestration for enterprise-grade use cases.
- Establish engineering guardrails for responsible AI, model selection, prompt patterns, evaluation metrics, hallucination controls, auditability, data privacy and secure enterprise integration.
- Drive reusable agentic accelerators, templates and platform services that improve developer productivity, standardise delivery and enable repeatable client solutions across sectors.
- Collaborate with cloud, data, security, UX and domain teams to industrialise AI agents into production-ready platforms with clear operating models, monitoring, fallback paths and human oversight.

Skills and attributes for success Must-have technical and leadership skills
- Python
- Java
- microservices
- architecture strategy
- API design
- DevOps/CI/CD
- production-readiness
- Microsoft Agent Framework
- LangGraph

📌 Tech S and T-Solution Architect-SM-G (Bengaluru)
🏢 EY
📍 Bengaluru