Senior Product Engineer

Albert Bow is partnering with a profitable, high-growth AI software company building a next-generation AI-native enterprise platform used by globally recognised organisations. Having already established strong recurring revenue, the company is now investing heavily into its core product: a platform designed to combine large language models and workflow automation into a unified system for automating complex business processes at scale. This is not an early experimentation-stage startup. The product is already deployed in production across enterprise environments, and the business is scaling rapidly with ambitious growth plans over the next few years. They are now looking to hire a Senior Product Engineer to help shape the technical direction of the platform as it enters its next phase of growth.

Role Overview

This is a senior individual contributor role focused on product engineering, system design, and AI-driven software development. You’ll work closely with a small, highly technical engineering team to define how the platform evolves across architecture, performance, and user-facing capabilities. The environment is highly autonomous and product-focused. Engineers are expected to operate close to real users, contribute directly to product direction, and own problems from discovery through to production. This role is suited to someone who enjoys combining deep technical execution with product thinking and wants high ownership without moving into formal management.

What You’ll Be Doing

• Deliver product across the full stack - from UI to backend services to the AI layer. You’ll move freely between areas and be responsible for everything you ship, all the way into production.
• Build and maintain LLM systems that sit at the heart of the product. That includes designing evals, tuning prompts, shaping agent behaviour, troubleshooting retrieval, and improving systems based on real-world performance.
• Work in an AI-first engineering setup. LLM tools, coding agents, eval-driven iteration, and fast experimentation are part of the normal development cycle, not optional extras.
• Own distributed systems in production. You’ll make decisions around architecture, scaling, reliability, latency, and cost - and be accountable for how those choices behave in the real world.
• Take unclear problems and turn them into executable plans. Break work down, define what matters, set boundaries, and make pragmatic trade-offs to keep things moving.
• Stay close to users and stakeholders. Gather raw feedback directly, interpret what’s actually needed, and translate it into engineering decisions.

What They’re Looking For

• Strong full-stack engineering experience, with depth in backend systems.
• Proven experience designing, building, and operating distributed systems in production.
• Strong Python experience, alongside familiarity with modern frontend frameworks (e.g. React / TypeScript).
• Hands-on experience shipping AI or LLM-powered systems beyond prototypes.
• Comfort working with evaluation systems, agent-based workflows, retrieval-augmented architectures, and production AI tooling.
• Strong ability to make architectural decisions in fast-moving, ambiguous environments.
• High product intuition and ability to work without clearly defined requirements.
• Regular use of modern AI-assisted development tools as part of day-to-day engineering practice.
• Typically 5+ years of engineering experience, though impact matters more than tenure.

Meaningful equity package. Hybrid working model (London). Pension. 25 days holiday. Modern office environment with strong engineering culture. High ownership and autonomy from day one.