Integration Lead

Job Summary

• Senior integration engineer or architect with hands-on enterprise integration depth.
• Has integrated intelligent systemsnot 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 firms AI reference architecture.

2. 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

• 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: Experience:

• 10+ years in a Global IT environment working with multiple disciplines