Senior Integration Developer Position Purpose Design and deliver enterprise integrations connecting core systems, digital platforms, and cloud services. Lead scalable, secure, AI-augmented architectures using MuleSoft Anypoint, Informatica Intelligent Data Management Cloud (IDMC), AWS Integration Services, and Azure Integration Services. Provide technical expertise from requirements through production support. Embed AI/ML in pipelines for transformation, anomaly detection, and predictive operations. Work with Product Managers, Enterprise Architects, and stakeholders on digital transformation and compliance. Deliver reusable shared capabilities, not one-off project assets. Principal Accountabilities 1. Integration Architecture & Design
• Design end-to-end solutions using API-led connectivity, event-driven architecture, and microservices.
• Lead reusable APIs, connectors, data mappings, and orchestration flows on MuleSoft Anypoint.
• Select suitable ETL/ELT, pub/sub, streaming, and batch patterns based on business needs and data volume.
• Define and enforce API governance: versioning, OAuth 2.0/mTLS security policies, and lifecycle management.
• Lead contract-first design with OpenAPI, AsyncAPI, or equivalent schema-first methods; define contracts before implementation.
• Define data contracts alongside API contracts, including data shape, freshness, quality thresholds, and producer-consumer lineage. 2. AI-Augmented Integration
• Embed AI/ML for data classification, intelligent routing, anomaly detection, and predictive data quality. Use cases include AI-driven eligibility support, operational-tool events, donor-health exception routing, and personalized donor engagement.
• Apply AWS AI services (SageMaker, Bedrock, Comprehend) and Azure AI/Cognitive Services to integration workflows.
• Partner with the AI/ML Product Engineer to operationalize ML and generative AI in Informatica and MuleSoft pipelines, using the shared AI operations layer (evaluation harnesses, observability, guardrails, prompt management) instead of parallel infrastructure.
• Implement AI-driven monitoring and self-healing to reduce manual intervention and MTTR. Manage inference cost as a core operational discipline through tiering, caching, and cost-per-outcome measurement. 3. Platform Development & Implementation
• Build, configure, and deploy integrations across MuleSoft Anypoint, Informatica IDMC, AWS (EventBridge, Step Functions, API Gateway, Lambda, Glue), and Azure (Logic Apps, Service Bus, Data Factory).
• Build and maintain ETL/ELT pipelines moving structured and unstructured data across cloud, on-premises, and SaaS systems.
• Implement real-time and batch integrations with ERP (SAP), CRM (Salesforce), LIMS, and donor-management platforms.
• Meet performance SLAs, throughput requirements, and high-availability standards.
• Contribute to the shared data platform initiative as an early pipeline contributor and consumer; help shape its data-contract and quality standards.
• Use progressive delivery patterns, including canary flows, dual-write, and shadow traffic, when migrating legacy integrations. Move capabilities from legacy platforms to purpose-built products with evidence-based safety nets, not single cutovers. 4. Security, Compliance & Quality
• Design integrations for applicable 21 CFR Part 11, HIPAA, GDPR, and cGMP requirements in plasma collection and life sciences.
• Encrypt, tokenize, and mask sensitive donor and clinical data in transit and at rest.




• Conduct code reviews, unit and integration tests; participate in GxP validation (IQ/OQ/PQ) and comply with the corporate Quality Management System (cQMS).
• Maintain technical documentation, including interface control documents (ICDs), data-flow diagrams, and runbooks.
• Build and maintain provider-consumer contract tests using Pact or equivalent. Contract tests complement integration tests and support independent service evolution across the product portfolio. 5. Monitoring, Operations & Continuous Improvement
• Implement end-to-end observability with centralized logging, distributed tracing (OpenTelemetry), and alerting (Splunk, Datadog, CloudWatch).
• Track health KPIs: error rates, latency, throughput, and uptime.
• Analyze root causes of integration failures and implement preventive measures.
• Evaluate emerging integration technologies, AI tools, and platform capabilities to evolve the integration landscape.
• Establish service-level objectives (SLOs) for error rates, latency, throughput, and availability. Use error budgets to balance reliability investment with delivery pace rather than treating reliability as simply up or down.
• Develop chaos engineering for critical flows. Inject controlled failures to verify graceful failure and safe recovery, complementing performance and observability work. 6. Stakeholder Collaboration & Technical Leadership
• Translate business and product requirements into technical specifications and integration designs.
• Mentor junior integration developers and analysts; lead knowledge-sharing and internal training.
• Participate in sprint planning, stand-ups, retrospectives, and backlog refinement.
• Clearly communicate integration risks, decisions, and architecture options to technical and non-technical audiences.
• Use AI coding assistants (Copilot, Cursor, Claude Code, or equivalent) in daily development. Help set acceptable-use standards for regulated data flows, integration prompt patterns, and code-review and quality gates for AI-generated code. Position Requirements Education
• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field; Master's preferred. Required Skills & Experience
• 7+ years of enterprise integration development, including at least 3 years in a senior or lead role.
• Hands-on MuleSoft Anypoint expertise (Mule 4, DataWeave, API Manager, Runtime Fabric); certification strongly preferred.
• Proficiency with Informatica IDMC, PowerCenter, or Cloud Data Integration.
• Deep AWS integration

experience:
API Gateway, EventBridge, Step Functions, Lambda, SQS/SNS, Kinesis, Glue, and S3.
• Azure integration

experience:
Logic Apps, Service Bus, API Management, Data Factory, and Event Grid.
• Strong API design and security knowledge: REST, GraphQL, AsyncAPI, OpenAPI/Swagger, and API security patterns.
• Working knowledge of AI/ML integration: embedding AI services in pipelines and using pre-trained LLMs, classification,



and NLP for enrichment and automation; familiarity with prompt-based integrations and RAG pipelines calling LLMs from integration flows.
• Event-driven and streaming architecture experience with Apache Kafka, AWS Kinesis, or Azure Event Hubs.
• Proficiency in at least two of Python, Java, JavaScript/Node.js, or Groovy.
• Strong data-format and transformation

skills:
JSON, XML, CSV, Avro, Parquet, and EDI.
• Familiarity with Docker, Kubernetes, and CI/CD (GitHub Actions, Jenkins, Azure DevOps).
• Experience integrating ERP (SAP S/4HANA), CRM (Salesforce), and SaaS applications through standard connectors and APIs.
• Strong integration security knowledge: OAuth 2.0, OpenID Connect, mTLS, API keys, and secrets management (AWS Secrets Manager, HashiCorp Vault).
• Strong problem-solving and troubleshooting across complex systems.
• Working knowledge of Pact, Spring Cloud Contract, or similar provider-consumer contract-testing tools.
• Familiarity with data-contract patterns/tools (dbt contracts, data-contract-cli, or equivalent), alongside API-contract discipline.
• Working knowledge of AI-assisted development tools (Copilot, Cursor, Claude Code, or equivalent), including regulated-environment acceptable-use standards and quality gates for AI-generated code.
• Integration delivery in regulated (life sciences, healthcare, financial services) or consumer-scale (retail, fintech, media) environments where reliability and data correctness matter. Willingness to learn 21 CFR Part 11, HIPAA, GxP, and donor-data privacy requirements.
• English B2+ or C1 Preferred Skills & Experience
• Direct integration experience in pharmaceutical, biotech, life sciences, or similarly regulated settings.
• Knowledge of healthcare/life-sciences data standards: HL7 FHIR, DICOM, or CDISC.
• Direct experience with 21 CFR Part 11, GxP, HIPAA, and GDPR validation in integration engineering.
• Exposure to iPaaS platforms such as Boomi, Workato, or Talend.
• Experience with data mesh, data fabric, or data lakehouse architectures.
• Generative AI experience in prompt engineering, RAG pipelines, and LLM orchestration (LangChain, AWS Bedrock Agents).
• Relevant certifications: AWS Solutions Architect, MuleSoft Certified Developer, Informatica PowerCenter Developer, or Azure Integration Services. Competencies
• Drives Innovation — identifies ways to apply AI and emerging integration technologies to complex business problems.
• Builds Collaborative Partnerships — builds trusted relationships across business, technology, and vendor teams.
• Ensures Quality & Compliance — upholds security, data integrity, and regulatory standards.
• Communicates with Impact — explains complex technical concepts clearly to senior leaders and non-technical partners.
• Develops Others — mentors junior colleagues and promotes continuous learning and technical excellence.
• Embraces Agility — adapts to changing priorities and iterative delivery.
• Reliability Ownership — owns reliability through SLOs, on-call presence, and error-budget discipline, keeping services trustworthy under load and change.
• AI Fluency — applies AI where it improves integration engineering and evaluates it critically; treats AI embedded in production flows with the same operational rigor as any production system, not as a novelty. Interested or know someone who fits? Send your resume to [email protected] or contact me directly. Share this opportunity with your network

📌 Senior Integrations Developer (Argentina)
🏢 Arkkosoft
📍 Argentina