Forward Deployed AI Engineer

Forward Deployed AI Engineer

Day rate: £700-£1,200 Outside IR35
Contract: Initial 12 months
Commitment: Approximately three days per week
Location: Two days per week onsite in London

Harnham is working with a leading private equity firm looking for a Forward Deployed AI Engineer to support businesses across its portfolio.

The portfolio is primarily made up of SMEs and scale-ups generating approximately £5m-£50m in annual revenue. These businesses operate across different sectors and have varying levels of technical maturity.

The role combines senior-level consulting with hands-on AI engineering. You will work directly with CEOs, boards and leadership teams to understand how their businesses operate, identify where AI can create genuine commercial value and then personally build and deploy the solutions.

The role

You will work across multiple portfolio companies, taking projects from initial discovery through to production delivery and adoption.

Responsibilities will include:

• Working directly with CEOs, boards and operational leaders.

• Understanding each company's commercial priorities, processes, systems and constraints.

• Identifying bottlenecks, repetitive work and opportunities for AI or automation.

• Translating business problems into clear technical requirements.

• Prioritising use cases according to commercial value, feasibility, cost and risk.

• Determining whether the right answer is AI, conventional automation, an existing product or a wider process change.

• Designing, building and deploying production AI applications.

• Developing LLM applications, RAG solutions, agentic workflows and process automation.

• Integrating solutions with existing APIs, databases, CRMs, document stores and operational platforms.

• Introducing appropriate evaluation, monitoring, security and guardrails.

• Supporting user testing, training and adoption.

• Measuring the commercial and operational impact of each implementation.

• Documenting solutions and leaving portfolio companies with maintainable systems.

• Working alongside a Fractional Chief Data Officer where data quality, governance or architecture issues need to be addressed.

What we are looking for

The successful person will combine strong consulting skills with genuine technical depth.

You should have:

• Previous experience working with private equity firms or PE-backed portfolio companies.

• Experience delivering within SMEs or scale-ups generating approximately £5m-£50m in annual revenue.

• Experience working directly with CEOs, boards, founders or investment stakeholders.

• Strong commercial discovery and process-mapping experience.

• The ability to identify and prioritise use cases based on business value.

• Strong hands-on Python and software-engineering skills.

• Recent experience personally building and deploying production AI applications.

• Commercial experience with LLMs, RAG, agentic AI or AI-driven workflow automation.

• Experience integrating AI applications with existing business systems and APIs.

• Experience taking projects from discovery and architecture through to deployment and adoption.

• Knowledge of cloud deployment, application monitoring, evaluation, security and cost management.

• The ability to operate independently across businesses with different systems and levels of technical maturity.

• Strong communication and stakeholder-management skills.

The balance of the role

This is not purely an advisory position, but it is also broader than a traditional AI engineering role.

You will need to be comfortable leading conversations with CEOs and boards, challenging assumptions and recommending where investment should be focused. You must then be able to move into the technical delivery, write the code, build the integrations and take the solution into production.

The strongest candidates are likely to come from Forward Deployed Engineering, applied AI consulting, technical founder, fractional CTO or hands-on AI leadership backgrounds.

Expected outcomes

The successful person will help the portfolio companies achieve:

• A prioritised pipeline of commercially valuable AI opportunities.

• Faster movement from initial idea to production deployment.

• Reduced manual and repetitive work.

• Improved employee productivity and operational efficiency.

• Better customer, sales and internal processes.

• Measurable improvements in revenue, margin, efficiency or customer experience.

• Secure, maintainable AI applications that can be adopted by the business.

• A clearer understanding of where AI is valuable and where simpler solutions are more appropriate.

Working arrangement

This is an initial 12-month fractional engagement requiring approximately three days per week.

Candidates must be able to work onsite in London two days per week, with the remaining time worked remotely. Some travel to portfolio companies may occasionally be required.