Senior Integration Developer (MuleSoft)

Senior Integration DeveloperFull Time (Hybrid)
Position Purpose
The Senior Integration Developer designs, develops, and delivers enterprise-grade integration solutions connecting core business systems, digital platforms, and cloud services. This role leads scalable, secure, and AI-augmented integration architectures using MuleSoft Anypoint, Informatica IDMC, AWS Integration Services, and Azure Integration Services.
The role serves as a technical SME across the integration lifecycle, from requirements analysis and architecture through development, deployment, monitoring, and production support. The developer will embed AI/ML capabilities into integration pipelines for data transformation, anomaly detection, intelligent routing, predictive data quality, and operational automation.
This role works closely with Product Managers, Enterprise Architects, AI/ML engineers, and business stakeholders. Integration assets are designed as reusable shared capabilities for multiple product teams rather than one-off project solutions.
Key Responsibilities
1. Integration Architecture & Design
Design end-to-end integration solutions using API-led connectivity, event-driven architecture, microservices, ETL/ELT, batch, streaming, and pub/sub patterns.Develop reusable APIs, connectors, data mappings, orchestration flows, and integration assets using MuleSoft Anypoint.Define API governance, including versioning, lifecycle management, OAuth 2.0, mTLS, and security policies.Apply contract-first integration using OpenAPI, AsyncAPI, or equivalent schema-first approaches.Define data contracts covering data structure, freshness, quality, and lineage.
2. AI-Augmented Integration
Embed AI/ML capabilities into integration pipelines for data classification, intelligent routing, anomaly detection, predictive data quality, and automation.Apply AWS AI services such as SageMaker, Bedrock, and Comprehend, as well as Azure AI/Cognitive Services.Integrate generative AI and ML capabilities into MuleSoft and Informatica pipelines while using shared AI operations infrastructure such as evaluation, observability, guardrails, and prompt management.Implement AI-driven monitoring and self-healing capabilities to reduce manual intervention and MTTR.Manage model inference costs through appropriate tiering, caching, and cost-per-outcome measurement.
3. Platform Development & Implementation
Develop, configure, and deploy integrations across MuleSoft Anypoint, Informatica IDMC, AWS, and Azure.Work with AWS services including API Gateway, EventBridge, Step Functions, Lambda, SQS/SNS, Kinesis, Glue, and S3.Work with Azure services including Logic Apps, Service Bus, API Management, Data Factory, and Event Grid.Build and maintain ETL/ELT pipelines across cloud, on-premises, and SaaS systems.Implement real-time and batch integrations with ERP/SAP, Salesforce, LIMS, donor management, and other enterprise platforms.Ensure integrations meet performance, throughput, availability, and reliability requirements.Contribute to shared data platform initiatives and data quality standards.Apply progressive delivery and migration patterns such as canary releases, dual-write, and shadow traffic.
4. Security, Compliance & Quality
Design integrations supporting applicable regulatory requirements including 21 CFR Part 11, HIPAA, GDPR, GxP, and cGMP.Protect sensitive donor and clinical data through encryption, tokenization, masking, and secure secrets management.Perform code reviews, unit testing, integration testing, and participate in GxP validation lifecycles such as IQ/OQ/PQ.Maintain technical documentation including interface control documents, data-flow diagrams, and operational runbooks.Implement contract testing using Pact, Spring Cloud Contract, or equivalent tools.
5. Monitoring & Operations
Implement end-to-end observability using centralized logging, distributed tracing, and monitoring tools such as OpenTelemetry, Splunk, Datadog, and CloudWatch.Monitor integration health through error rates, latency, throughput, uptime, and availability.Establish service-level objectives and use error-budget principles to balance reliability and delivery.Perform root-cause analysis and implement preventative measures.Introduce controlled failure testing and chaos engineering for critical integration flows.Continuously evaluate emerging integration technologies, AI capabilities, and platform improvements.
6. Collaboration & Technical Leadership
Translate business and product requirements into technical specifications and integration designs.Mentor junior developers and analysts and conduct technical knowledge-sharing sessions.Participate in Agile ceremonies, sprint planning, stand-ups, retrospectives, and backlog refinement.Clearly communicate technical risks, architecture decisions, and integration options to technical and non-technical stakeholders.Use AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or equivalent while following appropriate standards for regulated environments, code review, and quality gates.
Position Requirements
EducationBachelor's degree in Computer Science, Information Systems, Engineering, or related field.Master's degree preferred.
Required Skills & Experience
7+ years of enterprise integration development experience, including at least 3 years in a senior or lead role.Hands-on expertise with MuleSoft Anypoint Platform, including Mule 4, DataWeave, API Manager, and Runtime Fabric. MuleSoft certification strongly preferred.Experience with Informatica Intelligent Data Management Cloud (IDMC), PowerCenter, or Cloud Data Integration.Strong AWS integration experience with API Gateway, EventBridge, Step Functions, Lambda, SQS/SNS, Kinesis, Glue, and S3.Experience with Azure integration services including Logic Apps, Service Bus, API Management, Data Factory, and Event Grid.Strong understanding of REST, GraphQL, AsyncAPI, OpenAPI/Swagger, API governance, and API security.Working knowledge of AI/ML integration, including LLMs, classification, NLP, data enrichment, automation, prompt-based integrations, and RAG pipelines.Experience with event-driven and streaming architectures using Kafka, AWS Kinesis, or Azure Event Hubs.Proficiency in at least two of: Python, Java, JavaScript/Node.js, or Groovy.Strong knowledge of JSON, XML, CSV, Avro, Parquet, and EDI.Experience with Docker, Kubernetes, and CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.Experience integrating SAP/S4HANA, Salesforce, and SaaS platforms through APIs and standard connectors.Strong knowledge of OAuth 2.0, OpenID Connect, mTLS, API keys, and secrets management including AWS Secrets Manager or HashiCorp Vault.Experience troubleshooting complex multi-system integration environments.Working knowledge of contract testing using Pact, Spring Cloud Contract, or equivalent.Familiarity with data contract patterns and tools such as dbt contracts, data-contract-cli, or equivalent.Experience with AI-assisted development tools such as Copilot, Cursor, or Claude Code.Experience delivering integration solutions in regulated environments such as life sciences, healthcare, or financial services, OR consumer-scale environments where reliability and data correctness have significant business impact.Ability to work within regulated environments and build working knowledge of 21 CFR Part 11, HIPAA, GxP, GDPR, and applicable donor-data privacy requirements.
Preferred Skills & Experience
Pharmaceutical, biotech, healthcare, life sciences, or other regulated integration experience.Knowledge of HL7 FHIR, DICOM, or CDISC.Direct experience with 21 CFR Part 11, GxP, HIPAA, or GDPR validation requirements.Experience with Boomi, Workato, Talend, or other iPaaS platforms.Exposure to data mesh, data fabric, or data lakehouse architectures.Generative AI experience including prompt engineering, RAG, LLM orchestration, LangChain, or AWS Bedrock Agents.Certifications such as AWS Solutions Architect, MuleSoft Certified Developer, Informatica PowerCenter Developer, or Azure Integration Services.
Core Competencies
Drives Innovation: Applies AI and emerging integration technologies to solve complex problems.Builds Collaborative Partnerships: Works effectively across business, technology, and vendor teams.Ensures Quality & Compliance: Maintains high standards for security, data integrity, reliability, and regulatory compliance.Communicates with Impact: Explains complex technical concepts clearly to technical and non-technical audiences.Develops Others: Mentors team members and promotes continuous learning.Embraces Agility: Adapts to changing priorities in an iterative delivery environment.Reliability Ownership: Applies SLOs, monitoring, error budgets, and operational discipline to maintain reliable integrations.AI Fluency: Uses AI where it provides measurable value and applies production-level operational rigor to AI-enabled integration capabilities.