Integration Architect - MuleSoft
Key Skills for This Role
Full Job Posting
What you’ll do
- Architect and govern end-to-end MuleSoft Anypoint Platform solutions, defining Experience, Process, and System API layers following API-led connectivity principles
- Design and implement integrations connecting Salesforce Sales Cloud, Service Cloud, Health Cloud, Financial Services Cloud, and Marketing Cloud with ERP, data warehouse, and third-party platforms
- Lead the creation of architecture blueprints, technical roadmaps, integration standards documentation, and RAML/OAS API specifications
- Make technology decisions related to the MuleSoft and Salesforce integration environment, including connector strategy, authentication models, and deployment topology
- Work creatively and analytically with clients to understand business needs and create scalable integration solutions in a problem-solving environment
- Develop solutions for scalability while ensuring they conform to long-term strategic priorities and Salesforce Governor Limits
- Evolve and shape the strategy, architecture, platform, and standards for the integration team including CI/CD pipeline governance
- Specify and publish standards around APIs, DataWeave transformations, error handling, and retry policies on Anypoint Exchange
- Collaborate with Salesforce architects on Platform Events, Change Data Capture, and Salesforce Data Cloud pipeline strategies
- Be actively involved in pre-sales activities, effort estimation, and solution design for client-facing engagements
- Define the enterprise integration strategy and target-state architecture, choosing the right pattern for each use case (API-led, event-driven, streaming, batch/ETL, file-based) rather than defaulting to a single tool
- Design event-driven architectures using message brokers such as Anypoint MQ, Kafka, Azure Service Bus or AWS SNS/SQS/EventBridge, covering ordering, idempotency, replay and dead-letter handling
- Own the API lifecycle end to end, including design-first practices, versioning and deprecation, API catalogue management, Anypoint API Governance conformance and reuse through Anypoint Exchange
- Define integration security architecture, including API gateway policies, mTLS, secrets management, encryption in transit and at rest, PII handling and alignment with applicable data protection regulations
- Set non-functional requirements and design for performance, throughput, availability, disaster recovery, capacity and vCore sizing, and platform cost optimisation
- Establish observability and operational readiness, including logging standards, monitoring, alerting and distributed tracing (e.g. Anypoint Monitoring, Splunk, Datadog, OpenTelemetry), plus runbooks and SLAs for production support
- Define the integration testing strategy with QA, covering MUnit coverage, contract testing, end-to-end and performance testing, and test automation within CI/CD
- Shape data integration design, including canonical data models, mapping specifications, data quality rules, master data alignment and Salesforce Data 360 ingestion
- Lead legacy middleware modernisation and migrations (e.g. from TIBCO, webMethods or other ESBs, Mule 3 to Mule 4, and CloudHub 1.0 to CloudHub 2.0)
- Set up and run a Center for Enablement (C4E) and integration design authority, tracking reuse, standards adoption and delivery quality across projects
- Design APIs and integrations that AI agents can use safely, including exposing APIs as Agentforce actions and through Model Context Protocol (MCP) servers, with controls on access, rate limits and audit
- Modern ways of working with GenAI:
- Use AI-assisted development tools (e.g. AI features in Anypoint Code Builder, GitHub Copilot, Claude) to speed up Mule flow scaffolding, DataWeave transformations, RAML/OAS drafting and MUnit test generation, with architect-level review of everything produced
- Apply GenAI in discovery to analyse legacy interface documentation, WSDLs, schemas and code, producing interface inventories, mapping specifications and migration plans faster
- Use GenAI to draft and maintain architecture artefacts such as Architecture Decision Records, sequence diagrams (Mermaid/PlantUML), API catalogue descriptions and integration runbooks
- Bring AI into quality and operations through AI-assisted code reviews, policy and security conformance checks, synthetic test data generation, log analysis and incident root-cause summaries
- Design GenAI-enabled integrations that connect enterprise systems to LLM services (e.g. Amazon Bedrock, Azure OpenAI), including retrieval-augmented generation (RAG) patterns, prompt and response handling, and token cost governance
- Define and role-model responsible GenAI practices for the integration team: approved tools only, no client data or credentials in unapproved tools, human review of AI output, and clear ownership of anything that reaches production
Who you are
- Experienced professional who has designed and implemented a project’s end-to-end integration architecture using MuleSoft Anypoint Platform
- Able to work closely with clients to define and derive integration solutions aligned with business goals and Salesforce ecosystem capabilities
- Capable of guiding and mentoring a development team of MuleSoft and Salesforce integration engineers
- Strong understanding of Salesforce deployment and physical architecture including sandbox strategy, metadata API, and DevOps Center
- Experienced with different data and file standards including JSON, XML, CSV, EDI, and SOAP/REST interfaces
- Well-versed in Object-Oriented Architecture, RESTful API design, event-driven architecture, and asynchronous messaging patterns
- Comfortable navigating ambiguity and leading technical decisions in a fast-paced consulting environment
- A pragmatic, technology-agnostic architect who picks the right integration approach for the problem and can explain the trade-offs to business and technical audiences
- Commercially aware, with a view of total cost of ownership, platform licensing, reuse and long-term supportability when making design choices
- An early adopter of AI-assisted engineering who brings the team along, balancing productivity gains with quality, security and maintainability
- Experience defining the structure of integration systems, their interfaces, and the architectural principles that guide the client
- Strong skills in system documentation including ERDs, sequence diagrams, process flows, and API catalog management
- 10+ years of client-facing consulting or professional services experience in an integration or Salesforce architecture capacity
- Mandatory: 7+ years of experience designing, refining, and implementing MuleSoft Anypoint Platform solutions including CloudHub, Runtime Fabric, and hybrid deployment models
- Hands-on experience delivering on-premises and hybrid MuleSoft implementations, including Mule runtime installation and configuration, clustering and server groups, Runtime Manager agent setup, load balancing, network and firewall considerations, and patching and upgrades on customer-hosted infrastructure
- 3+ years of hands-on Salesforce integration experience spanning Sales Cloud, Service Cloud, and Salesforce Platform APIs (REST, SOAP, Bulk, Streaming)
- Experience with Anypoint MQ, Object Store, and event-driven integration using Salesforce Platform Events and Change Data Capture
- MuleSoft Certified Platform Architect – Level 1 and MuleSoft Certified Integration Architect – Level 1 required
- Experience working within cross-functional project teams to understand requirements and deliver scalable integration solutions
- Prior experience driving new points of view and capabilities in areas of API management, integration governance, and middleware strategy
- Experience with coding, testing, debugging, implementing, and documenting complex integrations using DataWeave 2.0, Java, and REST/SOAP patterns
- Familiarity with OAuth 2.0, JWT, SAML and security patterns for API and Salesforce connected app authentication
- Prior experience in management methodologies (waterfall, agile) enterprise planning, estimation, and project management (single and multi-site)
- Exposure to other integration platforms and services such as Boomi, Informatica, Azure Integration Services, AWS integration services or Kafka/Confluent
- Working knowledge of cloud platforms (AWS, Azure or GCP), containers and Kubernetes (including Runtime Fabric), and infrastructure as code such as Terraform
- Hands-on DevOps experience with Git, Maven and CI/CD tools (e.g. Jenkins, GitHub Actions, Azure DevOps), plus environment and release strategy for integration platforms
- Familiarity with modern API and event standards, including GraphQL, AsyncAPI, webhooks and gRPC
- Practical experience using GenAI tools in software engineering, with an understanding of LLM integration patterns (RAG, MCP, agent actions), prompt design and AI-specific risks such as prompt injection and data leakage
- The above description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
What you bring
- Preferred certifications: Salesforce Certified Integration Architect, Application Architect
- Additional preferred certifications: MuleSoft Developer (Level 1/Level 2), Salesforce Agentforce Specialist, or cloud architect certifications (AWS, Azure)
Preferred Qualifications
- Preferred certifications: Salesforce Certified Integration Architect, Application Architect
- Additional preferred certifications: MuleSoft Developer (Level 1/Level 2), Salesforce Agentforce Specialist, or cloud architect certifications (AWS, Azure)
- Salesforce Certified Integration Architect, Application Architect
- Experience working within cross-functional project teams to understand requirements and deliver scalable integration solutions
- Prior experience driving new points of view and capabilities in areas of API management, integration governance, and middleware strategy
- Experience with coding, testing, debugging, implementing, and documenting complex integrations using DataWeave 2.0, Java, and REST/SOAP patterns
- Familiarity with OAuth 2.0, JWT, SAML and security patterns for API and Salesforce connected app authentication
- Prior experience in management methodologies (waterfall, agile) enterprise planning, estimation, and project management (single and multi-site)
- Exposure to other integration platforms and services such as Boomi, Informatica, Azure Integration Services, AWS integration services or Kafka/Confluent
- Working knowledge of cloud platforms (AWS, Azure or GCP), containers and Kubernetes (including Runtime Fabric), and infrastructure as code such as Terraform
- Hands-on DevOps experience with Git, Maven and CI/CD tools (e.g. Jenkins, GitHub Actions, Azure DevOps), plus environment and release strategy for integration platforms
- Familiarity with modern API and event standards, including GraphQL, AsyncAPI, webhooks and gRPC
- Practical experience using GenAI tools in software engineering, with an understanding of LLM integration patterns (RAG, MCP, agent actions), prompt design and AI-specific risks such as prompt injection and data leakage
- The above description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
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