Lead Software Developer (AI Solutions)
Role details
Job location
Tech stack
Job description
We are seeking a highly motivated Lead Software Developer (AI) to lead the architecture, development, and implementation of AI-driven solutions supporting Data Management processes within a Clinical Research Organization (CRO). This role is ideal for a professional who can independently drive the full AI/software development lifecycle - from input into the identification of AI-automation opportunities to deployment of AI-components and supporting the team in maintaining production-ready solutions., * Participate in the identification of opportunities for AI-driven automation and process optimization
- Architecture, develop, and implement AI/ML solutions for Clinical Data Management and operational processes using LLMs, RAG, traditional ML techniques, and rule-based approaches
- Define and execute strategies for model development, testing, validation, benchmarking, and training data preparation
- Integrate AI solutions into existing desktop and web-based software platforms (primarily C#/.NET applications)
- Collaborate with cross-functional stakeholders to ensure alignment with regulatory, quality, and operational requirements
- Prepare and maintain technical documentation related to software applications, AI models, and development processes
- Stay current with advancements in AI, machine learning, and software engineering technologies, and proactively evaluate their applicability within the organization
Requirements
Do you have experience in Software deployment?, Do you have a Master's degree?, * Bachelor's degree in IT or an equivalent combination of education, training, and experience
- Minimum 5 years of practical experience in AI/ML/NN/computer vision solution development
- Minimum 2 years of experience building Generative AI and LLM-based solutions
- Proficiency in Python; SQL (MS SQL) and vector (Qdrant) databases; document-centric AI workflows
- Experience with AI validation, explainability, hallucination mitigation, benchmarking, and confidence scoring approaches
- Understanding AI-agent orchestration (MCP Server)
- Experience with APIs, CI/CD workflows, Git, Azure DevOps, and production deployment practices
- Understanding of SDLC and MLOP
Nice to Have
- Experience developing AI solutions within healthcare, life sciences, or CRO/pharmaceutical environments
- Experience integrating AI solutions into C#/.NET enterprise platforms
- Familiarity with Selenium, Playwright, or other automated testing frameworks