Role Overview
We are seeking a hands-on AI Developer to design, build, and deploy AI and machine learning solutions that support the Medical Smart Initiative (MSI) and Medical Analytics platforms. You will work closely with data scientists, data engineers, and software engineers to operationalise predictive models and generative AI capabilities for analytics, decision support, and intelligent automation.
This role is ideal for an experienced developer with strong Python skills and practical experience building production-grade machine learning and generative AI applications on AWS.
Key Responsibilities
AI Application Development
- Develop, test, and deploy machine learning and generative AI solutions for medical analytics and decision support use cases.
- Build APIs and application services to integrate AI capabilities into MSI and Medical Analytics platforms.
- Implement Retrieval-Augmented Generation (RAG), prompt orchestration, and agent-based workflows where appropriate.
- Develop reusable components and libraries to accelerate AI solution delivery.
Model Operationalisation
- Deploy machine learning models using AWS SageMaker and integrate foundation models through Amazon Bedrock.
- Implement automated pipelines for model inference, evaluation, and retraining.
- Optimise model performance, scalability, and cost efficiency in production environments.
- Monitor model quality, latency, and usage metrics.
Data Preparation & Integration
- Collaborate with data engineers to prepare and transform structured and unstructured datasets.
- Build preprocessing pipelines for feature engineering, embeddings, and document ingestion.
- Integrate AI services with enterprise applications and data platforms.
Testing & Quality Assurance
- Develop unit, integration, and evaluation tests for AI applications.
- Implement guardrails and validation checks for generative AI outputs.
- Troubleshoot issues across data pipelines, models, and application services.
Collaboration & Continuous Improvement
- Work closely with solution architects and business stakeholders to translate requirements into technical solutions.
- Stay current with emerging AI technologies, tools, and best practices.
- Contribute to coding standards, documentation, and reusable engineering practices.
Required Skills & Experience
- 3+ years of software development experience, with at least 2 years building AI/ML applications.
- Strong proficiency in Python and modern software engineering practices.
- Experience deploying machine learning solutions to production.
- Familiarity with REST APIs, microservices, and cloud-native development.
- Strong problem-solving and debugging skills.
Technical Skills
- Python
- AWS SageMaker
- Amazon Bedrock
- LangChain or similar orchestration frameworks
- TensorFlow, PyTorch, or Scikit-learn
- FastAPI, Flask, or Django
- Docker and Kubernetes
- Git and CI/CD pipelines
Preferred Experience
- Experience building RAG applications, chatbots, and AI copilots.
- Exposure to vector databases such as Pinecone, Weaviate, or OpenSearch.
- Experience in healthcare, medical analytics, or other regulated environments.
- Understanding of model evaluation, prompt engineering, and responsible AI practices.
