We are seeking an expert Integration Developer to design, implement, and optimize end-to-end integrations across our US Healthcare Revenue Cycle Management (RCM) platform. This role focuses on integrating AI/ML, GenAI, LLM Ops, Agentic AI, RPA, and cloud-based microservices into seamless, automated workflows.
The ideal candidate combines hands-on technical expertise with a deep understanding of Healthcare RCM modules (Claims, Prior Authorization, Coding, Collections, Scheduling, EDI), ensuring high-performance, compliant, and scalable integrations.
Integration Architecture & Development:
- Design and implement end-to-end integration solutions between AI/ML platforms, RPA tools, cloud services, and enterprise systems.
- Develop microservices-based APIs, RESTful and event-driven interfaces, and serverless functions for seamless workflow orchestration.
- Enable data flow between AI/ML models, autonomous agents, and RCM modules, ensuring real-time and batch processing.
- Optimize integration performance, latency, and scalability across cloud platforms (AWS, Azure, GCP).
AI/GenAI & Agentic AI Integration:
- Collaborate with Data Scientists and AI Engineers to integrate LLMs, GenAI models, and autonomous agents into production workflows.
- Enable multi-agent orchestration pipelines for AI-driven decision-making and automation.
- Ensure auditability, logging, error handling, and governance for AI/Agentic AI integrations.
RPA & Automation Integration:
- Work with RPA developers to embed AI predictions and agent outputs into automated workflows across RCM processes.
- Monitor and troubleshoot RPA-ML pipelines, ensuring seamless orchestration and performance.
- Implement robust exception handling, transaction rollback, and recovery mechanisms for automated workflows.
Data Engineering & Pipeline Support:
- Collaborate with Data Engineers to integrate ETL/ELT pipelines, Big Data platforms, and cloud-native data services into applications.
- Ensure data quality, compliance (HIPAA, SOC 2, GDPR), and lineage for integrated systems.
- Support real-time data streaming pipelines (Kafka, Spark, Flink) and batch processes feeding AI/ML models.
Collaboration & Mentorship:
- Partner with Product, AI/ML, Data, DevOps, and QA teams to design and implement integration solutions aligned with business goals.
- Mentor junior Integration Developers and technical teams on best practices in API design, AI integration, RPA orchestration, and cloud workflows.
- Provide technical documentation, architecture diagrams, and standard operating procedures for integration projects.
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Software Engineering, or related fields.
- 6–12+ years of experience in system integration, middleware development, or enterprise software integration.
- Proven expertise integrating AI/ML, LLMs, Agentic AI, and RPA workflows into production systems.
- Experience with cloud platforms (AWS, Azure, GCP), microservices, REST APIs, and serverless architectures.
- Strong understanding of Healthcare RCM workflows and compliance requirements (HIPAA, SOC 2, GDPR).
Technical Expertise:
- Programming & Scripting: Python, Java, C#, SQL, Scala
- Integration & Middleware: REST APIs, SOAP, JSON, XML, API Gateway, Kafka, RabbitMQ, MuleSoft, Dell Boomi
- Cloud Platforms & Services: AWS Lambda, SageMaker, Bedrock, Azure Functions, Azure Logic Apps, GCP Cloud Functions
- RPA Tools: UiPath, Automation Anywhere, Blue Prism integration
- Data Engineering & Big Data: Spark, Hadoop, Snowflake, Redshift, Airflow, dbt
- AI/ML & Agentic AI Integration: LLM Ops, multi-agent orchestration, autonomous workflows
- DevOps & CI/CD: Jenkins, Git, Docker, Kubernetes, Terraform, CI/CD pipelines for integrations
Skillset:
- Strong problem-solving and analytical skills for complex enterprise integrations.
- Expertise in end-to-end integration of AI/ML, Agentic AI, RPA, and cloud workflows.
- Ability to design scalable, secure, and compliant integration solutions in healthcare environments.
- Excellent collaboration, documentation, and communication skills with technical and non-technical stakeholders.
- Knowledge of best practices for monitoring, logging, and error recovery in production integrations.
Strategic Impact:
- Deliver scalable and compliant integrations for AI/ML-driven Healthcare RCM platforms.
- Enable autonomous agent workflows, RPA orchestration, and AI/GenAI adoption across RCM processes.
- Optimize data flow, AI model consumption, and real-time automation pipelines for operational efficiency.
- Establish integration standards, architecture best practices, and governance frameworks across the enterprise.
Kindly Note: At Credence, we uphold the highest standards of integrity in our recruitment process. We do not charge any fees at any stage of the hiring process, and we strictly prohibit any third parties, vendors, or individuals from soliciting money in exchange for job opportunities at Credence.
If you are approached by anyone requesting payment or offering you a position at Credence in exchange for money, do not engage with them. Such actions are fraudulent and not authorized by Credence. Please report any such incidents immediately to our official HR team at [email protected]
Your safety and trust are important to us. Thank you for helping us maintain a fair and transparent hiring environment.
