Position: Lead Product Engineer
Company: Bridge Innovation — Bridge LLC
Location: Scotland, UK (Remote)
Type: Full-time
Reports to: Head of Innovation
About Bridge Innovation
Bridge Innovation is the product studio within Bridge LLC. We design, prototype, and launch new software products at the intersection of design-led thinking, AI-assisted development, and deliberate product strategy. The team is small, autonomous, and moves fast.
We are design-led, not engineering-led. That means the engineer we hire needs to be someone who thrives in an environment where product thinking and user experience drive technical decisions — not the other way around. You will not be handed a spec and asked to build it. You will be at the table when we decide what to build and why.
The Role
This is the most strategically important hire for Bridge Innovation in 2026. You will own technical vision and architecture across all products in the studio’s pipeline. You will be the person who turns validated product concepts into real, shippable software — and who makes the technical decisions that determine whether a product can scale, be acquired, or needs to be killed.
You will work directly with the Head of Innovation (product and strategy) and Lead Product Designer (design and prototyping) as the third point of a small, high-trust team. As the studio grows, you will lead and shape the engineering function.
Key Responsibilities
* Technical architecture: Own architecture decisions across all Bridge Innovation products. Select appropriate stacks for each product based on its stage, audience, and likely exit path (acquisition, internal retention, or spin-out). Document and defend these decisions clearly.
* Hands-on building: This is a building role, especially in year one. You will write code, set up infrastructure, build APIs, and ship features. You are not directing from above — you are in the code.
* AI/LLM integration: Several products in the pipeline involve AI and LLM components in production. You need to architect, build, and maintain these integrations — including prompt engineering, model selection, API integration, cost management, and handling the specific reliability and safety challenges of AI in production systems.
* Build scope judgment: Know when to prototype fast and when to build for production. Know when to use a managed service and when to build bespoke. Know when a product should be killed on technical grounds and say so clearly.
* Feasibility assessment: Evaluate the technical feasibility of new product concepts during early validation stages. Provide honest, evidence-based assessments — not just “yes, we can build that” but “here’s what it would actually take, here’s what’s hard, and here’s what changes if we want it in six weeks vs. six months.”
* Engineering credibility: Represent Bridge Innovation’s technical work to the wider Bridge engineering organisation. Explain, argue, and defend architectural decisions peer-to-peer with senior engineers who may have a different philosophy about how software should be built.
* Team leadership: As the studio grows, hire, mentor, and lead other engineers. Establish engineering standards, review processes, and development practices for the studio.
Requirements
Qualifications & Experience
* 7+ years of professional software engineering experience, with at least 2 years in a senior or lead capacity.
* Proven experience building and shipping production systems — not just prototypes, not just internal tools, but products used by real customers.
* Demonstrated experience with AI/LLM systems in production: building products that use language models, embeddings, or generative AI as core functionality (not just experimentation or side projects).
* Experience making architecture decisions across multiple products or services, including technology selection, infrastructure design, and scalability planning.
* Experience leading, mentoring, or managing other engineers.
Knowledge & Skills
* Full-stack generalism: You are not a narrow specialist. You can work across frontend, backend, infrastructure, and data. You don’t need to be expert in all of them, but you need to be able to evaluate, build, and make sound decisions across the stack.
* AI/LLM production fluency: You have built real products with AI components. You understand the practical challenges: prompt engineering, model selection and cost, latency, reliability, safety, evaluation, and the difference between a demo that works and a production system that doesn’t break.
* AI-assisted development: You actively use AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) in your own workflow. You see these as tools that amplify good engineering judgment, not replacements for it, and not threats to be resisted.
* Pragmatic decision-making: You optimise for the right thing at the right time. You know when technical debt is acceptable and when it isn’t. You can articulate trade-offs clearly to non-technical stakeholders.
* Communication and collaboration: You can explain technical concepts, constraints, and trade-offs to designers and product thinkers who are not engineers. You can defend a position in a room without being defensive. You listen to product and design input and let it genuinely shape your technical approach.
* Commercial awareness: You think about products, users, and business outcomes, not just code quality. You understand that the goal is a product someone will buy or acquire, and you make engineering decisions accordingly.
* Independence and initiative: You work with significant autonomy. You don’t wait for detailed specs. You identify what needs to be done, propose an approach, and execute.
What This Role Is Not
* A narrow specialist position — we need breadth across frontend, backend, infrastructure, and AI.
* A traditional enterprise engineering role with detailed specifications and fixed roadmaps handed to you.
* A role where you direct others but don’t build yourself.
* A role where engineering drives product decisions — design and product thinking lead here, and the right engineer is energised by that, not frustrated by it.
Preferred Background
* Experience in a startup, studio, agency, or early-stage product environment where you wore multiple hats.
* Familiarity with Shape Up (Basecamp/Ryan Singer) or similar appetite-based development methodologies.
* Experience building products intended for acquisition rather than indefinite scaling.
* Track record of working closely with designers and product thinkers — not just other engineers.
* Experience with any of: Next.js/React, Swift/SwiftUI, Python, Node.js, Cloudflare Workers, Supabase, or similar modern product stacks.