Position Summary
As a Senior AI Software Engineer and member of a dynamic, multi-functional Agile development team, you will play a pivotal role in embedding AI-enabled capabilities into our core applications and software development operations. You will leverage modern AI development tools, including Microsoft Foundry (formerly Azure AI Foundry), agent orchestration frameworks (Semantic Kernel, LangChain/ LangGraph, LlamaIndex), and GitHub Copilot, to accelerate development, transform user experiences, and automate complex workflows across laboratories and clinical environments.
You will collaborate with product managers, UX designers, and data scientists to deliver AI-enabled, GenAI, and agentic solutions that drive customer productivity. You will also work with process stakeholders to AI-enable workflows within the SDLC, including user-story generation, code generation, test automation, and PR automation.
To excel in this role, you must demonstrate a genuine passion for quality software, dedication to customer satisfaction, and the ability to work effectively in a matrix organization. Practical experience using AI tools to accelerate software development is essential.
Clinisys' AI Philosophy:
Building an AI‑first organisation is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI‑enabled, cloud‑based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and testing environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI‑enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve, must drive an AI first sense of purpose and urgency.
Essential Functions
AI Development & Integration
- Design and implement AI features across the SDLC and Clinisys products to support agentic and generative workflows
- Build and deploy AI-powered solutions using Microsoft Foundry, including model selection, prompt flow development, and endpoint management
- Design and implement agentic AI workflows using orchestration frameworks such as Semantic Kernel, LangChain, and LangGraph, including multi-agent coordination, tool calling, and autonomous task execution
- Develop and integrate LLM-powered capabilities such as intelligent assistants, natural language query builders, and contextual help systems
- Implement Retrieval-Augmented Generation (RAG) systems to address domain-specific requirements in laboratory and clinical workflows
- Apply prompt engineering strategies to optimize LLM responses and user interactions
AI-Accelerated Software Development
- Leverage GitHub Copilot within VS Code and Visual Studio to accelerate code development, refactoring, and documentation
- Establish and promote best practices for AI-assisted development workflows across the team
- Create agentic workflows for SDLC automation including code generation, test automation, and PR review assistance
- Monitor AI tool effectiveness and iterate on prompts and workflows to improve developer productivity
Software Development
- Build solutions using Python, JavaScript/Typescript, C#, or similar languages as needed.
- Develop front-end interfaces using React, Angular, or similar frameworks
- Build back-end services using Python (FastAPI/Flask), C# .NET, and MS Entity Framework
- Work with relational and NoSQL databases including Oracle, PostgreSQL, MSSQL, Azure Cosmos, MongoDB, Dynamo, and Redis
- Scaffold and maintain APIs using controller-service-repository or similar architectural patterns
- Ensure robust testing coverage including unit, integration, and performance tests
Operations & Quality
- Ensure secure handling of AI inputs/outputs, including prompt data, embeddings, and model responses
- Implement observability practices including logging, tracing, and monitoring for AI services
- Monitor model and application performance post-deployment, and iterate on prompts, retrieval, and evaluation as needed
- Troubleshoot and resolve integration and deployment challenges
- Document technical specifications, integration workflows, and architectural decisions
Collaboration
- Collaborate with various internal teams to deliver intelligent, user-centric experiences
- Mentor other developers and promote best practices in AI integration
- Contribute to AI governance initiatives and responsible AI practices
Required Skills & Experience
AI Tools & Platforms (Primary)
- Hands-on experience with Microsoft Foundry for building and deploying AI solutions
- Experience with agent orchestration frameworks (Semantic Kernel, LangChain, LangGraph, LlamaIndex) for building multi-step, tool-calling AI workflows
- Proficiency with GitHub Copilot in VS Code or Cursor and/or Visual Studio for AI-assisted development
- Experience with LLM APIs (Azure OpenAI, OpenAI, Anthropic, AWS Bedrock)
- Understanding of RAG architecture and implementation, limitations and strategies to improve response quality
- Experience working with embeddings and vector stores (Azure AI Search, Cosmos DB, PostgreSQL)
- Familiarity with document ingestion pipelines and chunking strategies for optimal retrieval
- Strong prompt engineering skills
- Familiarity with AI gateway patterns and multi-provider model routing for managing LLM traffic across Azure OpenAI, Anthropic, and AWS Bedrock endpoints
Development Skills (Nice to have)
- Strong proficiency in Python for AI/ML development, API services, and data pipelines
- Proficiency in TypeScript/Javascript and front-end frameworks (React preferred, Angular acceptable)
- Proficiency in C# and .NET development
- Experience with relational databases (Oracle, MSSQL, PostgreSQL) and NoSQL databases (MongoDB, Cosmos, Dynamo, Redis)
- Familiarity with REST API design and implementation
- Git Version control with Azure Devops, GitHub or similar products
General
- Strong debugging, analytical, and problem-solving skills
- Excellent verbal and written communication
- Collaborative mindset with the ability to mentor and lead by example
- Deep understanding of agile software development methodologies
- Comfortable working across time zones with distributed teams
Preferred Skills
- Knowledge graph experience with RAG (GraphRAG, LightRAG, Graphiti, Neo4j, PostgreSQL).
- Familiarity with how LLMs work under the hood (transformers, embeddings) and awareness of their limitations, fine tuning concepts
- Experience with AI-specific observability: LLM tracing, token usage monitoring, prompt/response logging, and cost attribution (e.g., LangSmith, Weights & Biases, Microsoft Foundry tracing, or similar)
- Background in healthcare, laboratory software, or LIS/LIMS systems
- Experience creating agents and workflows using Microsoft Copilot Studio
Required Experience & Education
- Bachelor’s degree in software engineering, Computer Science, or related field
- 5+ years of full-stack software development experience
- 2-3 years of hands-on experience building AI/LLM-powered applications, agents, or developer tooling
Preferred Experience & Education
- Master’s degree in computer science or related discipline
- Experience with scientific data software, medical devices, healthcare, or laboratory systems
- Familiarity with LIS/LIMS platforms
- Knowledge of regulatory frameworks including HIPAA, CLIA, GDPR, and accessibility standards
- Experience with healthcare interoperability protocols (HL7, FHIR, ASTM)
- Experience working with globally distributed teams
- Relevant certifications (Azure AI Engineer Associate, Google ML Engineer)
Supervisory Responsibilities
None
