Integration Lead - Enterprise AI Systems

EY; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Ernst & Young LLP ( EY India ) in Bengaluru seeks an Integration Lead to own and evolve the enterprise integration layer, enabling agentic AI systems to interoperate with enterprise platforms. You will focus on scalable, secure, and observable integration patterns across tools and data.

As a senior engineer/architect, you will work with API-based and event-driven approaches, define contracts, support both custom-built and platform-based orchestrators, and drive governance for reusable

Qualifications

• Experience designing enterprise integration patterns (API, event-driven, asynchronous, microservices).
• Experience with agent-to-agent communications and orchestration frameworks.
• Familiarity with MCP and A2A concepts.

Responsibilities

• Design and standardize enterprise integration patterns for agentic AI solutions.
• Enable A2A interoperability using standardized protocols and contracts.
• Integrate and extend orchestration SDKs for agent coordination and workflow execution.
• Design MCP-enabled integrations to standardize discovery of tools and APIs.
• Lead enterprise system and platform integration with identity, access management, and audit logging.
• Define reusable integration blueprints and governance standards for EY.

Skills

Core integration expertise

Agentic & orchestration exposure

API design

Cloud-native engineering

Education

Degree in Computer Science / Engineering

Tools

Orchestration SDKs

Enterprise integration tooling

Job description

Integration Lead - Bangalore At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY Job Description

Job Title: Integration Lead Asst. Director EY Technology | CBS Technology | Intelligent Automation

Reports to (Job Title): AI Engineering Lead

Job Summary: The Integration Lead will own and evolve the enterprise integration layer that enables agentic AI systems to interoperate reliably with each other and with enterprise platforms. This role is central to scaling agentic AI beyond isolated solutions- ensuring consistent integration patterns, governed access to tools and data, and seamless agent-to-agent and agent-to-system communication. Senior integration engineer or architect with hands-on enterprise integration depth. Has integrated intelligent systems—not just applications. Thinks in protocols, contracts, and control boundaries, not point solutions. Pragmatic: able to support both custom-built and platform-based agent ecosystems. Without a strong integration layer: Agents remain siloed and fragile Orchestrators become tightly coupled and hard to scale MCP and agent interoperability cannot be realized This role ensures agentic AI becomes a connected, enterprise-grade capability, not a collection of disconnected automations.

Essential Functions of the Job:

• Enterprise Integration Architecture for Agentic Systems — Design and standardize integration patterns for agentic AI solutions, including: API-based integration Event-driven and asynchronous messaging patterns Hybrid deterministic + AI-driven flows Ensure integrations align with enterprise resilience, scalability, observability, and security standards, as reflected in the firm’s AI reference architecture.
• Agent-to-Agent (A2A) Interoperability — Enable agent-to-agent operability using standardized communication protocols and contracts. Implement and promote A2A communication patterns that allow agents to: Discover, collaborate, delegate tasks, and exchange context Operate across heterogeneous frameworks and vendors Align A2A implementations with emerging internal standards and protocol specifications.
• Orchestrator & SDK Integration — Integrate and extend leading orchestration SDKs and frameworks used for agent coordination, routing, and workflow execution. Support integration between: Custom-built orchestrators Platform-based orchestrators (e.g., enterprise AI and automation platforms) Partner closely with orchestration and platform teams to ensure clean separation between control plane (orchestration) and integration plane (connectivity).
• Model Context Protocol (MCP) Enablement — Design and implement integrations with MCP servers to standardize how agents: Discover tools and services Invoke enterprise APIs and data sources Operate through a governed, observable contract layer Contribute to MCP adoption as a foundational integration mechanism across the agent ecosystem.
• Enterprise System & Platform Integration — Lead integration of agentic solutions with the enterprise application ecosystem, including: Core business systems, data platforms, automation tools, and third-party services Ensure consistent use of identity, access management, audit logging, and policy enforcement across integrations, aligned with AI governance expectations.
• Integration Governance & Reusability — Define reusable integration blueprints, templates, and accelerators for agentic solutions. Prevent fragmented, point-to-point agent integrations by enforcing: Common contracts Versioning strategies Dependency and lifecycle management Partner with AI governance and architecture forums to institutionalize integration standards.

Knowledge and Skills Requirements:

• Core Integration Expertise — Deep experience designing and implementing enterprise integration patterns (API, event-driven, asynchronous, microservices-based). Proven experience integrating complex distributed systems in large enterprises.
• Agentic & Orchestration Exposure — Practical understanding of agent-to-agent communication concepts and interoperability challenges. Experience integrating with orchestration frameworks or SDKs used to coordinate AI workflows. Familiarity with emerging protocols such as Model Context Protocol (MCP) and A2A concepts.
• Platform & Engineering Skills — Strong API design skills (REST, eventing, contracts, schemas). Experience working with cloud-native services and enterprise integration tooling. Comfort operating across AI engineers, orchestration leads, security teams, and platform owners.

Job Requirements:

Education: A degree in Computer Science / Engineering or a related discipline; or equivalent work experience

Experience: 10+ years in a Global IT environment working with multiple disciplines to deliver projects in line with customer needs 3+ Years Global delivery or transformation preferably in large scale infrastructure programs 3+ Years in a global operations environment

Certification Requirements: Microsoft Certified: Azure AI Engineer Associate (AI 102) Microsoft Certified: Azure Solutions Architect Expert (AZ 305) Enterprise architecture or distributed systems certifications (e.g., TOGAF).

EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Experience Level Senior Level