AI ML/Integration Engineer

Shearwater CPO® - Home of Clinicians; Philippines; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

Shearwater CPO® - Home of Clinicians is seeking an ML Integration Engineer to deploy and operationalize ML solutions across the enterprise. You will design scalable APIs, build ML-enabled services, and drive end-to-end MLOps for secure AI delivery.

You will collaborate with Data Science, Software, and DevOps teams to ensure governance, performance, and reliability while enabling AI capabilities aligned with business goals.

Qualifications

• Graduate or Master’s Degree with 5 years in Information technology, Computer science Engineering with healthcare experience (2+ years).
• 3–8 years of experience in software development, ML engineering, or AI integration.
• Strong programming skills in Python, Java, C#, or Node.js.
• Experience integrating RESTful APIs, GraphQL, or gRPC services.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of Docker and Kubernetes.
• Experience with CI/CD tools such as GitHub Actions, Azure DevOps, Jenkins, or GitLab CI.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
• Experience with SQL and NoSQL databases.
• Strong understanding of software architecture, distributed systems, and microservices.

Responsibilities

• Integrate ML models into web, mobile, and enterprise applications.
• Design and develop APIs and microservices to expose ML capabilities.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and DevOps teams to deploy AI solutions.
• Build and maintain CI/CD pipelines for ML model deployment (MLOps).
• Optimize model inference performance, latency, and scalability.
• Deploy ML solutions on cloud platforms such as AWS, Azure, or Google Cloud.
• Monitor production ML systems for performance, availability, and drift.
• Troubleshoot integration issues and improve system reliability.
• Implement security controls for AI applications, including authentication and data privacy.
• Integrate AI services like LLMs, Generative AI, NLP, and Computer Vision into business apps.
• Develop automation workflows using APIs, event-driven architecture, and messaging platforms.
• Maintain technical documentation, deployment guides, and architecture diagrams.
• Ensure compliance with enterprise security, governance, and regulatory requirements.

Skills

Python

Java

C#

Node.js

RESTful APIs

GraphQL

Cloud computing

Education

Bachelor's or Master's degree in Computer Science / IT / AI or related field

Graduate or Master’s Degree with 5 years IT experience including healthcare

Tools

Docker

Kubernetes

GitHub Actions

Azure DevOps

Jenkins

GitLab CI

Job description

The ML Integration Engineer is responsible for enabling the seamless deployment and operationalization of Machine Learning solutions across the enterprise. This role integrates ML models into production environments, develops scalable APIs and services, and automates end-to-end MLOps workflows to ensure efficient, reliable, and secure AI delivery. Working closely with Data Science, Software Engineering, and DevOps teams, the ML Integration Engineer ensures that AI capabilities align with business objectives, meet performance and quality standards, and comply with governance requirements. The role also drives solution validation, monitoring, documentation, and continuous improvement to support the sustainable adoption of AI technologies across the organization.

Responsibilities

• Integrate Machine Learning models into web, mobile, and enterprise applications.
• Design and develop APIs and microservices to expose ML model capabilities.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and DevOps teams to deploy AI solutions.
• Build and maintain CI/CD pipelines for ML model deployment (MLOps).
• Optimize model inference performance, latency, and scalability.
• Deploy ML solutions on cloud platforms such as AWS, Azure, or Google Cloud.
• Monitor production ML systems for performance, availability, and model drift.
• Troubleshoot integration issues and improve system reliability.
• Implement security controls for AI applications, including authentication, authorization, and data privacy.
• Integrate AI services such as Large Language Models (LLMs), Generative AI, NLP, and Computer Vision into business applications.
• Develop automation workflows using APIs, event-driven architecture, and messaging platforms.
• Maintain technical documentation, deployment guides, and architecture diagrams.
• Ensure compliance with enterprise security, governance, and regulatory requirements.

Business Requirements Management

• Gather, analyze, and document business requirements from stakeholders.
• Conduct workshops, interviews, and requirement elicitation sessions.
• Translate business needs into functional and non-functional requirements.
• Prepare Business Requirement Documents (BRDs) and Functional Requirement Specifications (FRS).

Project Support

• Support project planning, estimation, and prioritization activities.
• Assist Project Managers in scope management and change control.
• Participate in Agile ceremonies, sprint planning, and backlog grooming.
• Track project deliverables and business outcomes.

Solution Validation & Testing

• Develop user stories, acceptance criteria, and test scenarios.
• Support User Acceptance Testing (UAT).
• Validate solutions against business requirements.
• Coordinate issue resolution and defect tracking.

Reporting & Documentation

• Prepare business reports, dashboards, and presentations.
• Maintain project documentation and knowledge repositories.
• Develop training materials and user guides.
• Support change management and end-user adoption activities.

Qualifications

• Graduate or Master’s Degree with 5 years in Information technology, Computer science Engineering with at least 2+ years in healthcare (CPO/BPO, payer, provider, or health tech).
• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field.
• 3–8 years of experience in software development, ML engineering, or AI integration.
• Strong programming skills in Python, Java, C#, or Node.js.
• Experience integrating RESTful APIs, GraphQL, or gRPC services.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of containerization using Docker and Kubernetes.
• Experience with CI/CD tools such as GitHub Actions, Azure DevOps, Jenkins, or GitLab CI.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
• Experience with databases including SQL and NoSQL.
• Strong understanding of software architecture, distributed systems, and microservices

Required Skills

• PMP, PRINCE2, Agile / Scrum Certifications, ITIL and Lean Six Sigma
• Familiarity with productizing AI/ML and agentic systems in healthcare operations
• Frameworks: TensorFlow, PyTorch, Scikit-learn, Fast API, Flask
• CI/CD: Jenkins, GitHub Actions, GitLab CI