Principal Forward Deployed AI Engineer

Working style: Hands-on and customer-facing

We are ideally looking for a FDE who has end to end AI delivery experience, ideally AWS or GCP Native and worked in a forward deployed or consulting environment working with enterprise clients.

We’re hiring a Principal Forward Deployed Engineer for a growing AI technology startup. The business is running from its own cash flow, giving it the stability of an established operation while retaining the pace and ownership of an early-stage company.

This role sits across engineering, product and customer delivery. You’ll work directly with enterprise customers to understand complex problems, design practical solutions and take them all the way through to production.

This isn’t an advisory or architecture-only position. You’ll remain hands-on across the full stack and take genuine ownership of delivery.

What you’ll do

• Own important customer and product initiatives from discovery through to production
• Work directly with enterprise stakeholders to understand problems and shape solutions
• Lead architecture and implementation across frontend, backend and cloud infrastructure
• Build integrations between the platform and customer systems
• Make key technical decisions and remain accountable after launch
• Work closely with product, design and customer-facing teams
• Improve standards across code quality, security, performance and reliability
• Strengthen development workflows, CI/CD, monitoring and operational processes
• Mentor engineers and help grow the wider team’s technical capability
• Use AI development tools and agents to improve delivery speed and quality

What we’re looking for

You’ll be an experienced technical leader who can point to significant products or customer outcomes you have personally delivered.

We’re particularly interested in people who can demonstrate:

• End-to-end ownership of complex software delivery
• Strong customer-facing and consultative problem-solving skills
• Hands-on experience designing and building cloud-native, full-stack applications
• Deep knowledge of distributed systems, data modelling and API design
• Strong skills in Python, Type Script or similar modern languages
• Experience with public cloud platforms and infrastructure as code
• Knowledge of CI/CD, Dev Ops, observability and production reliability
• The ability to influence technical decisions across teams
• A practical, outcome-focused approach to engineering

AI-assisted development is central to how this team works.

You should have practical experience using AI coding agents as part of your normal engineering workflow—not simply experimenting with basic coding assistants.

You’ll be able to explain:

• How you plan and structure work for AI agents
• How you prompt, review and verify generated work
• The guardrails you use to protect quality and security
• Where AI improves your productivity
• Where experienced engineering judgement still needs to lead

You’ll also help establish effective AI development practices across the engineering team.

Current technology

The current environment includes:

• Type Script and React
• Python and FastAPI
• PostgreSQL and analytical databases
• AWS OR GCP (ideally AWS Native)
• Terraform and cloud development frameworks
• Git Hub Actions

Experience with every technology is not required. Strong engineering fundamentals, systems thinking and the ability to learn quickly are more important.

Nice to have

• Experience in a high-growth startup or scale-up
• Experience building large enterprise or multi-tenant platforms
• Knowledge of AI, machine learning, LLMs or speech technology
• Public technical contributions through Git Hub, technical writing or speaking
• Circa $250,000 salary plus equity
• Join a startup funded through its own cash flow
• Take ownership of meaningful enterprise-scale AI products
• Work directly with customers on complex real-world problems
• Remain hands-on while influencing architecture and product direction
• Help shape the engineering culture and AI development practices
• Join at a stage where your decisions will have a visible impact
• Receive genuine technical autonomy

The interview will focus on real examples rather than hypothetical questions.

Come prepared to discuss a project you personally owned, the obstacles you faced, the decisions you made and what ultimately reached production. You’ll also be asked about how you use AI agents in your development workflow and how you’ve solved complex problems directly with customers.