AI Software Engineer

Job Description Clinisys is a leading global provider of intelligent informatics solutions, offering advanced technologies and expert services that transform modern laboratory operations across diverse sectors such as healthcare, life sciences, public health, environmental testing, water quality, toxicology, and contract services. Through its platform and cloud-based solutions, Clinisys empowers over 3,000 laboratories in 34 countries to generate millions of analytical and diagnostic results, and data insights every day, supporting more efficient and effective workflows for laboratories and testing environments worldwide.

Headquartered in Tucson, Arizona, and Woking, England, Clinisys’ mission is to enhance the effectiveness of diagnostic workflows in any laboratory or testing environment and keep citizens and communities healthier and safer.

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.

Purpose (of The Role) As an AI Software Engineer and a member of a dynamic and multi-functional Agile development team, you will play a pivotal role in embedding AI-enabled capabilities into our core applications, software development operations, transforming user experiences and automating complex workflows across laboratory and clinical environments. To excel in this role, you must demonstrate a genuine passion for quality software, dedication to customer happiness, and the ability to work effectively in a matrix organization.

Practical experience in deploying AI solutions in a Production environment is essential. Your hands-on experience using GenAI tools—such as ChatGPT, Copilot, etc. and your familiarity with the latest versions of popular LLMs such as Claude or GPT-X—as well as a strong foundational understanding of other AI domains (NLP, Predictive Analytics, Computer Vision) will be instrumental in creating operational efficiencies and commercialized product features.

You will collaborate with product managers, UX designers, and data scientists to deliver AI-enabled, GenAI, and agentic solutions for our customers to help drive their productivity. You will collaborate with process stakeholders to ensure processes within the SDLC are AI-enabled, creating agentic workflows were needed, which can include user-story generation, code-generation, test-automation, PR automation etc.

You will own the development, deployment, and integration of AI services, ensuring they meet performance, security, and compliance standards. Your work will directly influence the scalability, innovation, and intelligence of Clinisys’ next-generation software solutions.

Essential Functions

• Design and implement AI features across the SDLC and Clinisys products to support agentic and generative workflows.
• Develop and integrate LLM-powered capabilities such as intelligent assistants, natural language query builders, and contextual help systems.
• Fine-tune and implement large language models (LLMs), as well as Retrieval-Augmented Generation (RAG) systems (e.g., Claude, GPT-X), to address domain-specific requirements in laboratory and clinical workflows.
• Monitor model performance post-deployment and implement retraining strategies to maintain accuracy and relevance.
• Apply prompt engineering strategies to optimize LLM responses and user interactions.
• Ensure secure handling of AI inputs/outputs, including prompt data, embeddings, and model responses, in alignment with global data privacy regulations.
• Implement observability practices including logging, tracing, and monitoring for AI services.
• Build full-stack solutions using object-oriented programming, preferably with:
• Front-End: HTML, CSS, React, Angular, JavaS…