Senior Software Engineer - AI First
Cluepoints
Software Engineering, Data Science
United Kingdom
Company Description
At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster.
We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 40 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA.
At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way. Guided by our values of Care, Passion, and Smart Disruption, we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide.
We’re looking for an AI-First Software Engineer Engineer to help shape this next chapter.
The Role
As an AI-First Engineer, you will operate at the intersection of strong software engineering fundamentals and modern AI-assisted development. You will use state-of-the-art AI coding tools (e.g., Claude Code, GitHub Copilot, Codex-style agents) to generate and iterate on production-grade code — while applying human judgment, architectural thinking, and rigorous review to ensure quality, security, and compliance.
As part of our AI-First transformation, we are adopting Spec-Driven Development (SDD) across our engineering teams. Instead of moving straight from user stories into code, engineers write structured specifications that serve as the single source of truth for both human and AI-driven implementation. The spec is reviewed and approved before any code is written, and AI coding agents work within the constraints it defines.
Some of our squads are already working this way, and these roles will help scale the approach across the organisation. Experience with SDD frameworks such as OpenSpec, SpecKit, BMAD, or Superpowers is required.
This is not a traditional “ticket-driven” engineering role. Instead, you will:
- Work in small, high-impact squads (4–5 people)
- Operate within a Spec-Driven Development (SDD) framework
- Treat AI as a powerful collaborator — not a replacement for engineering responsibility
- Focus on integration, edge cases, system-level thinking, and production robustness
- Your output will be amplified by AI — but your judgment will define its quality.
- 5+ years of professional software engineering experience shipping production systems
- Proficiencyin Python (essesntial) and/or TypeScript (experience with both is ideal)
- Hands-on, daily use of AI coding assistants in real delivery workflows
- Demonstrated ability to critically evaluate AI-generated code:identifyinghallucinations, security risks, architectural drift, and edge cases
- Solid understanding of API design (REST), relational databases (MySQL or equivalent), and at least one NoSQL store
- Strong testing discipline: unit, integration, and end-to-end testing as part of your normal workflow
- Experience with Spec-Driven Development frameworks such asOpenSpec,SpecKit, BMAD, or Superpowers
- Comfort working in a regulated or compliance-sensitive environment, or willingness to learnGxPexpectations quickly
Strong Advantage
- Experience with Angular or a modern frontend framework
- Experience building structured AI-assisted workflows (prompt pipelines, agent orchestration, automated review systems)
- Microsoft Azure cloud experience
- Background in life sciences, healthcare, or other regulated industries
Bonus
- Contributions to open-source AI tooling or developer productivity projects
- Experience with CI/CD pipeline design and DevOps practices
- Familiarity with clinical trial data, CDISC standards, or RBQM concepts
Our Technology Stack
- Languages: Python
- Frontend: Angular/Typescript
- Data: MySQL, Parquet, Databricksand MongoDB
- Cloud: Microsoft Azure
- AI Tooling: Claude Code, GitHub Copilot, and other AI coding assistants integrated into daily workflows
Note* You do not need deep experience in every part of this stack, but you should be comfortable working across backend and frontend and confident in ramping quickly on unfamiliar technologies — with AI as an accelerator, not a crutch.
AI-Assisted Implementation
- Use AI coding tools to generate and iterate on implementation code
- Rapidlyprototypemultiple technical approaches with AIassistance
- Ensure AI-generated output meetsCluePoints’ engineering standards before submission
Spec-Driven Development
- Work from approved specifications as thesingle sourceof truth
- Collaborate with Product Managers and Tech Leads to refine technical scope
- Implement features according to reviewed and approved specs
- Maintain traceability between requirements, implementation, and tests
Architecture, Integration & Production Ownership
- Handle complex integration points and system-level concerns
- Address edge cases and performance considerations AI may miss
- Contribute to architectural discussions and long-term technical decisions
- Monitor productionbehaviorof AI-accelerated systems and proactively address stability, observability, and performance issues
Quality & Compliance
- Review AI-generated code before raising pull requests
- Increase andmaintaintest coverage through automated testing
- Ensure outputs are secure, auditable, and aligned with regulatory expectations (GxPcontext)
- Participate in code reviews and continuous improvement of engineering standards
Continuous Improvement
- Experiment with new AI tools and workflows to increase productivity
- Contribute to evolvingCluePoints’ AI-First engineering practices