Ocho
Technical Lead
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AI Tech Lead – Contract
Location: London / Hybrid – 2 days per week
Contract: Initial 6 months
IR35: Outside IR35
Rate: Up to £750 per day
Start: October 2026
Ocho is working with a major global payments organisation that is building a new AI Innovation capability within its Enterprise business.
We are looking for an AI Tech Lead to identify high-value business problems, assess where AI or automation can add value, and rapidly turn the strongest ideas into working prototypes and proofs of value.
This is not a traditional programme, transformation or engineering management role.
The focus is on:
- Hands-on AI innovation
- Rapid problem solving
- Short delivery cycles
- Evidence-led experimentation
The successful candidate will work directly with business teams, structure ambiguous problems, identify the most appropriate technical approach and help prove whether an idea works before it enters a formal Product or Engineering delivery process.
The Role
You will sit at the intersection of technology consulting, applied AI and rapid product delivery. The role is highly autonomous and suited to someone who is comfortable moving quickly from:
- Business problem → Technical hypothesis → Prototype → User feedback → Proof of value.
You will work closely with Commercial, Operations and other Enterprise teams to identify opportunities where AI, automation or emerging technologies could improve revenue, speed, efficiency or customer outcomes.
The emphasis is not on producing long strategy documents or running large-scale programmes. Instead, you will:
- Understand the problem
- Assess the available technical options
- Prototype quickly
- Test with users
- Measure the result
- Decide whether to progress, change direction or stop
Successful concepts will then be handed into Product, Engineering and Data teams for formal productionisation.
Key Responsibilities
- Work directly with business stakeholders to identify high-value AI and automation opportunities
- Break down ambiguous business problems using a structured, first-principles approach
- Translate business pain points into practical and testable technology solutions
- Assess the most appropriate technical approach, including:
- Generative AI
- Agentic AI
- Machine learning
- Workflow automation
- APIs
- Existing enterprise platforms
- Third-party tools
- Simpler non-AI solutions
- Define hypotheses, success criteria and measurable business outcomes
- Rapidly create or help create proofs of concept and proofs of value
- Work closely with a hands-on AI Innovation Specialist to turn ideas into working prototypes
- Use AI-assisted development and modern delivery approaches to accelerate experimentation
- Test prototypes with users and incorporate feedback quickly
- Evaluate technical feasibility, commercial value and time-to-value
- Make evidence-based recommendations on whether initiatives should progress, pivot or stop
- Assess new AI tools, platforms and technologies against the organisation’s existing stack
- Identify capability gaps and recommend external tools where appropriate
- Hand successful pilots into Product and Engineering teams with clear evidence, requirements and learning
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What We’re Looking For
The strongest candidates will come from a technology, digital, data or AI consulting background and will still be close to hands-on delivery. We are particularly interested in people who have worked in recognised consulting environments such as:
- Deloitte
- Accenture
- Capgemini
- IBM Consulting
- PwC
- EY
- KPMG
- McKinsey
- Bain
- Oliver Wyman
- BCG
- Similar Tier 1 / Tier 2 technology or strategy consultancies
The consulting background is important because this role requires someone who is comfortable with:
- Ambiguity
- Short, high-intensity engagements
- High expectations for delivery
- Structured problem solving
- First-principles thinking
- Strong stakeholder communication and presentation
However, this is not a strategy-only consulting role. The successful candidate must still be sufficiently technical and hands-on to work closely with modern AI tools and rapid prototype development.
Essential Experience
- Strong background in technology, digital, data or AI consulting
- Experience solving ambiguous business problems in fast-moving environments
- Strong understanding of where AI can and cannot add value
- Hands-on experience with modern AI tools, prototypes, agents or AI-enabled workflows
- Experience moving rapidly from an idea to a proof of concept or proof of value
- Strong structured problem-solving and consulting skills
- Experience working directly with business stakeholders and technical teams
- Strong presentation and communication skills
- Good understanding of modern product and software delivery approaches
- Strong commercial awareness and ability to quantify potential value
- Ability to assess multiple technical options rather than defaulting to an LLM for every use case
- Comfortable working independently with limited structure
Technology Environment
Direct experience with every platform is not required, but relevant experience with comparable enterprise AI technologies is important. The current environment includes:
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- AWS Bedrock
- Salesforce Agentforce
- Microsoft Copilot and Microsoft ecosystem
- Databricks
- Snowflake
- Cursor
- Enterprise LLM tooling
- AI-assisted development environments
- Modern data and automation platforms
Experience with equivalent technologies is transferable.
The key requirement is the ability to understand new tools quickly and determine where they can create practical value.
Ideal Candidate Profile
A strong candidate is likely to have:
- Around 5–10+ years of relevant technology, product, data or AI consulting experience
- Recent hands-on exposure to GenAI, agentic AI or AI-assisted development
- Experience working directly with clients or internal business teams
- A track record of moving from ambiguous problems to working solutions
- Experience delivering in short, agile cycles
- Strong technical fluency without necessarily being a career software engineer
- Enough technical depth to challenge and work effectively with engineers, data scientists and AI specialists
- Strong commercial judgement
- A pragmatic approach to:
- Build vs buy
- AI vs conventional automation
- Prototype vs production
- Continue vs stop
The ideal person will be able to walk into an unfamiliar business problem, understand it quickly, determine the right technical approach and produce something testable in a short period of time.
What This Role Is Not
This is not primarily a:
- Programme Manager role
- Transformation Director role
- PMO role
- Enterprise Architecture role
- Traditional Engineering Manager role
- AI Governance-only role
- Strategy-only consulting role
We are not looking for someone who has moved too far away from delivery.
The strongest candidates will still be close to the technology, current AI tools and hands-on experimentation.
What Success Looks Like
Over the six-month engagement, success will be measured by:
- Building a strong pipeline of viable AI and automation opportunities
- Rapidly delivering multiple prototypes and proofs of value
- Demonstrating measurable business value through experimentation
- Progressing the strongest pilots into formal Product and Engineering delivery
- Stopping weak ideas early based on evidence
- Identifying gaps in the current technology stack
- Recommending relevant new tools and technologies
- Significantly reducing the time from business problem to testable solution
The person we are looking for should be able to combine consulting-quality problem solving with modern, hands-on AI delivery.
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