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

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

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📌 Senior Integrations Developer (MuleSoft, AWS and Azure) (Argentina)
🏢 Arkkosoft
📍 Argentina