AI-First Software Engineer

AI-First Software Engineer

About CluePoints

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 organisations 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.

Guided by our values of Care, Passion, and Smart Disruption, we are evolving our engineering model to become an AI-First organisation — leveraging modern AI coding tools and Spec-Driven Development to accelerate delivery while maintaining the highest quality and regulatory standards.

We’re looking for an AI-First Engineer to help shape this next chapter.

Role Overview

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.

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.

How We Work

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.

Our Technology Stack

CluePoints products are built on:

• Languages: Python

• Frontend: Angular/Typescript

• Data: MySQL, Parquet, Databricks and MongoDB

• Cloud: Microsoft Azure

• AI Tooling: Claude Code, GitHub Copilot, and other AI coding assistants integrated into daily workflows

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.

Job Requirements

Must Have

• 5+ years of professional software engineering experience shipping production systems

• Proficiency in Python 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: identifying hallucinations, 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 as OpenSpec, SpecKit, BMAD, or Superpowers

• Comfort working in a regulated or compliance-sensitive environment, or willingness to learn GxP expectations 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

Key Responsibilities

AI-Assisted Implementation

• Use AI coding tools to generate and iterate on implementation code

Rapidly prototype multiple technical approaches with AI assistance

• Ensure AI-generated output meets CluePoints’ engineering standards before

submission

Spec-Driven Development

• Work from approved specifications as the single source of 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 s 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 production behavior of AI-accelerated systems and proactively address stability, observability, and performance issues

Quality s Compliance

• Review AI-generated code before raising pull requests

• Increase and maintain test coverage through automated testing

• Ensure outputs are secure, auditable, and aligned with regulatory expectations (GxP context)

• Participate in code reviews and continuous improvement of engineering standards

Continuous Improvement

• Experiment with new AI tools and workflows to increase productivity

• Contribute to evolving CluePoints’ AI-First engineering practices

What Success Looks Like

• Faster feature delivery without increased production defects

• High-quality pull requests requiring minimal rework

• Strong alignment between specifications, implementation, and tests

Production systems that remain stable, observable, and maintainable despite accelerated AI-driven delivery

• Clear, defensible technical decisions — even when AI assisted

• Continuous improvement of AI workflows within the squad

How to Apply

This is not a traditional engineering role, and we don’t want a traditional application.

When you apply, please include one example that demonstrates how you work in an AI- assisted development environment. This could be:

• A project or feature where AI tools played a significant role in delivery

• A pull request where you iterated with an AI coding assistant

• A structured workflow you built using prompts, specifications, or agent orchestration

• A short write-up explaining how you use AI tools in production We care less about polish and more about how you think.

Specifically, we’re interested in:

• How you define constraints before prompting

• How you evaluate and refine AI-generated output

• How you maintain quality, security, and maintainability

• How AI changes your engineering workflow and, where it doesn’t

If you’ve contributed to AI tooling, prompt libraries, spec frameworks, or developer

productivity improvements, feel free to share those as well.