Senior Middleware, Integration & AI Architect

Context

As a Senior Middleware, Integration & AI Architect, you will play a leading role in shaping the future integration ecosystem, ensuring that traditional integration capabilities evolve towards highly automated, cloud-native and AI-enabled platforms.

Mission

The Senior Middleware, Integration & AI Architect is responsible for defining the future integration ecosystem by combining traditional integration architecture expertise with emerging capabilities around cloud transformation, automation, platform engineering and artificial intelligence.

The architect will play a key role in enabling a future where enterprise integrations, APIs and AI-driven agents can be deployed, governed and operated in a highly automated, secure and scalable manner, while maintaining the strong governance and reuse principles that have historically made the Middleware Architecture practice successful.

The architect will help project teams to understand the integration architecture and respect the standard in place to easy and accelerate integration setup respecting middleware and security governance.

Key Responsibilities

Integration Architecture & Governance

• Lead the architecture of enterprise integration solutions for strategic business initiatives.
• Define and evolve architecture principles, standards and reference patterns for APIs, events, process orchestration and cloud integrations.
• Support Solution Architects and Project Teams during architecture design and implementation phases.
• Participate in governance boards and architecture review processes.
• Promote API reuse, domain ownership and platform standardization.
• Align integration architecture with Enterprise Architecture and Security Architecture roadmaps.

API Strategy & Platform Evolution

• Drive API-first and Platform-first approaches throughout the organization.

• Define standards for:

• API Design

• API Security
• Lifecycle Management
• Versioning
• Documentation
• Developer Experience
• Support the evolution of API Management and Integration Platforms.
• Contribute to the adoption of industry standards such as TM Forum Open APIs and OpenAPI specifications.
• Evaluate emerging technologies and integrate them into architectural roadmaps.

AI & Intelligent Integration Architecture

A major objective of this role is to prepare the integration landscape for the rise of Generative AI and Agentic Systems.

You will:

• Define how Large Language Models (LLMs) can safely interact with enterprise systems.
• Design integration patterns enabling AI agents to discover, invoke and compose enterprise services.
• Define governance frameworks for AI-enabled integrations.

• Evaluate emerging standards such as:

• Model Context Protocol (MCP)

• Agent-to-Agent integration patterns
• AI Tool Calling frameworks
• AI Gateway architectures
• Define architectural principles for exposing enterprise capabilities to AI agents through secure and governed APIs.
• Collaborate with Security and Enterprise Architecture teams to establish guardrails preventing uncontrolled AI access to critical systems.
• Contribute to the definition of enterprise AI integration strategies and target operating models.
• Support business teams in identifying opportunities where AI agents can augment or automate complex business processes.

The architect is expected to remain continuously informed on developments in AI, LLM ecosystems, agent orchestration frameworks and emerging integration standards.

Integration as Code & Middleware Automation Architecture

Automation of middleware provisioning and governance is a strategic pillar of the future integration platform.

You will:

• Define the target architecture enabling "Integration as Code" practices.
• Design end-to-end automation of middleware setup and onboarding processes.
• Drive initiatives aiming to reduce manual engineering effort through platform automation.
• Define requirements for self-service integration platforms.
• Design governance-driven automation pipelines ensuring compliance by default.

• Collaborate with platform engineering teams to establish automated deployment models for:

• APIs

• Security policies
• Access controls
• Certificates
• Routing configurations
• Event subscriptions
• Integration services
• Define and maintain enterprise guardrails ensuring that automated deployments remain secure and compliant.

• Contribute to automation initiatives leveraging:

• GitOps

• Infrastructure as Code
• Policy as Code
• Configuration as Code
• Platform Engineering principles
• Act as a key architecture stakeholder in projects building orchestration solutions and automated deployment frameworks.
• Define non-functional requirements around auditability, traceability and governance of automated changes.

A key objective of this role is to transform middleware onboarding from an engineering-intensive process into a highly automated and governed platform capability.

Cloud Native & Platform Architecture

• Drive transformation from legacy integration platforms towards cloud-native solutions.

• Define reference architectures leveraging:

• Azure Integration Services

• Azure API Management
• Kubernetes / AKS
• Service Mesh technologies
• Event Streaming Platforms
• Cloud-native Security Services
• Support migration strategies from legacy middleware environments.
• Participate in Proof of Concepts and platform evaluations.

Security & Compliance

• Define security architectures for APIs, integrations and AI-enabled services.
• Collaborate with security teams to implement enterprise security standards.

• Establish secure patterns around:

• OAuth2

• OpenID Connect
• JWT
• mTLS
• IAM
• Zero Trust principles
• Ensure compliance with regulatory and internal governance requirements.
• Define security controls for LLM access to enterprise services and data.

Operational Excellence & Observability

• Define platform requirements around:

• Resilience

• Scalability
• Performance
• Availability
• Observability
• Promote modern operational practices based on monitoring, tracing and automated operations.
• Support integration of observability capabilities into automated deployment pipelines.

Required Skills

Integration & Architecture

• Extensive experience in Enterprise Integration Architecture.

• Strong expertise in:

• API Management

• SOA
• Event-Driven Architecture
• Enterprise Service Bus
• Business Process Management
• File Transfer & ETL
• Integration Patterns
• Distributed Systems
• Microservices
• Experience defining governance frameworks and operating models.

Cloud & Platform Engineering

Strong knowledge of:

• Azure cloud services
• Azure API Management
• Kubernetes / AKS
• Service Mesh (Istio)
• GitOps methodologies
• Infrastructure as Code
• Policy as Code
• CI/CD platforms
• Platform Engineering concepts
• Springboot framwork

Some knowledge of :

• Aurea Sonic ESB
• IBM BAW & IID (Business Process Management)

AI & Emerging Technologies

Good understanding of:

• Generative AI concepts
• Large Language Models
• Agentic Architectures
• Model Context Protocol (MCP)
• AI governance principles
• Secure AI integration patterns

Security

Strong understanding of:

• OAuth2
• OpenID Connect
• JWT
• mTLS
• IAM
• API Security
• Zero Trust Architecture
• Certificate management, PKI

Soft Skills

• Leadership and influencing skills
• Strategic thinking and vision
• Excellent communication and presentation skills
• Strong stakeholder management capabilities
• Facilitation and consensus-building skills
• Coaching and mentoring mindset
• Strong analytical and problem-solving abilities
• Innovation and continuous learning mindset
• Pragmatic and results-oriented approach
• Ability to lead change and transformation initiatives
• Collaboration and teamwork
• Ability to manage complex discussions and conflict resolution
• Adaptability in fast-changing environments
• Autonomous and proactive attitude
• Strong sense of ownership and accountability