Albert Bow
Founding Product Engineer
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Founding Product Engineer
Lead Product Engineer – AI Research & Decision Intelligence Platform
Albert Bow is partnering with a profitable, high-growth AI software company, developing a next-generation research and decision intelligence platform used by globally recognised brands and enterprises.
The company has successfully established a commercial base with strong recurring revenue and is now rapidly scaling its AI platform, merging large language models with workflow automation into a unified operating system for clients.
This is not an experimentation-stage startup—the product is already in production, and the company has ambitious growth plans for the coming years.
About the Role
Lead Product Engineer – highly autonomous senior role focused on architecture, product engineering, and AI systems design. You’ll collaborate with a small team of technical engineers to define the technical trajectory of the platform as it enters its accelerated growth phase.
This environment demands deep technical expertise combined with strategic product thinking. Engineers must operate near the customer, shape product direction, and own entire projects—from concept to live deployment. This role suits individuals who enjoy blending deep technical execution with high-level strategy, desire meaningful ownership without managerial responsibilities, and thrive in fast-moving, high-impact settings.
Responsibilities
Core Technical Leadership
- Write and deploy strictly production-grade code, covering backend services, AI-driven workflows, and end-user features.
-Define and uphold system architecture across AI infrastructure, frontend applications, and cloud-based systems, ensuring scalability, robustness, and maintainability.
-Build and maintain production-level LLM systems, including:
- Orchestration layers for multi-agent workflows
- Retrieval pipelines optimised for reliability
- Evaluation tooling for monitoring and refining AI performance
- Comprehensive system observability for real-time diagnostics Partner closely with Product and commercial teams to translate live customer pain points into scalable, production-ready solutions. Allocate cross-functional priorities based on stakeholder needs.
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Engineering Quality & Roadmap
- Define and enforce elevated engineering standards for:
- Testing, deployments, and systems reliability
- Code reviews, monitoring, and governance best practices
- Balance rapid iteration with long-term scalability, ensuring technical debt doesn’t hinder future growth.
- Proactively identify architectural constraints and scaling risks, feeding insights into strategy discussions.
Growth & Mentorship
- Cultivate peer engineers through technical leadership:
- Code reviews with rigorous feedback
- Knowledge-sharing via pairing sessions and informal mentorship
- Driving up collective engineering capabilities
Customer-Centric Ownership
- Engage directly with end users (enterprise customers) to:
- Deliberate workflows and identify pain points
- Surface friction as actionable requirements
- Shape product direction aligned with real-world usage data
Requirements
- 6+ years of senior engineering experience, but results and impact matter more than tenure.
- Demonstrated strength as a full-stack engineer with expertise in backend systems.
- Proven hands-on experience in building and operating distributed production systems, including:
- AWS/Gcloud environments
- Real-scale site reliability engineering (SRE) practices
- Performance optimisation beyond proof-of-concept stage
- Technical depth in AI/ML: Experience shipping systems based on:
- Large Language Models (LLMs)
- Retrieval-augmented architectures
- Agent-based workflow design
- MLoPs in production
- Versatile with AI-centric tooling including vector databases, observability platforms, and evaluation mechanisms.
- Python as core language, with fluency in:
performance-oriented APIs (e.g., FastAPI) scalability patterns (e.g., microservices) batch processing/pipeline management - Familiarity with modern frontend frameworks (React/TypeScript) and tooling.
- Strong product intuition—ability to navigate ambiguous technical reqs and derive solutions without prescriptive guidance.
- Active adoption of AI-assisted dev tools (e.g., Copilot) as part of daily workflow.
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Technology Stack
Python (FastAPI, LangGraph), React (TypeScript), Kubernetes, GCP, Redis, PostgreSQL, Datadog
Package & Benefits
- Core remuneration: £130,000 – £140,000 p.a.
- Equity: Meaningful package reflecting leadership potential.
- Location: Hybrid working model (basis London).
- Perks:
- Private health insurance
- Company pension scheme
- 25 days annual leave
- Culture: Modern office space with technical depth, high autonomy, and a culture prioritising engineering excellence. Approaches decision-making with the speed and rigor of a startup, scales with domain strength.
Note: The role stresses individual contribution and ownership but offers pathways for mentorship-first collaboration with peers. Position is non-managerial in structure, though it conferred with senior stakeholder engagement.
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