AI Engineering Director

Posted 2 Days Ago
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London, England, GBR
In-Office
Expert/Leader
Database • Analytics
The Role
Lead discovery and prioritisation of AI opportunities, translate them into value cases and roadmaps, and drive solutions from validation through deployment. Mobilise cross-functional teams, assess technical feasibility and data readiness, establish governance for responsible AI and delivery, and present recommendations to executive stakeholders to realise measurable business outcomes.
Summary Generated by Built In
Company Description

Our Mission

Blend is an award-winning pure play data consultancy who help people do data right through project delivery across strategy and consulting, data science and BI, and data engineering. As a trusted Data & AI partner we co-create value with clients across a wide variety of industries. Our company has made the Inc. 5000 list of Fastest Growing Companies and currently have offices in Edinburgh, the US, Uruguay, and India. We are an accredited “Great Place To Work” company across all our office locations, with a shared and active focus on DEI initiatives and championing representation in all aspects of our work.

By combining our teams’ expert technical knowledge with a practical approach to value creation, we deliver outcomes that make a real change for our clients. From using computer vision to remotely monitor crops to implementing a BI dashboard to help swimmers win more medals – nothing we do is designed to be left on the shelf.

Job Description

This role is ideal for a senior leader who can turn complex business challenges into focused, scalable AI opportunities with clear and measurable impact.

As AI Product & Strategy Consultant, you will operate at the intersection of business strategy, technology and delivery. You will work with investment partners, executive committees and senior operating leaders to identify where value sits, determine when AI is the right answer and shape practical solutions that can move from discovery into delivery.

You will combine executive presence with enough technical depth to challenge assumptions, assess feasibility and direct cross-functional teams. Success requires sound judgement, comfort with ambiguity and a bias towards action without losing sight of quality, scalability, cost or risk.

Responsibilities

  • Lead discovery across business functions, using interviews, workshops and analysis to uncover the underlying problem rather than accepting the presenting issue at face value.
  • Identify and prioritise AI, data and workflow opportunities according to commercial value, operational impact, feasibility and delivery risk.
  • Translate opportunities into clear value cases, prioritised roadmaps, implementation plans and measurable success criteria.
  • Shape AI-enabled products and solutions from initial point of view through validation, build, deployment and adoption.
  • Design phased programmes that deliver near-term value while establishing reusable data, technology and operating foundations.
  • Redesign workflows and operating models by understanding how people work, where judgement sits and what drives behaviour, not only how systems and processes are documented.
  • Work alongside engineers, data scientists and architects to test assumptions, validate data and technical feasibility, and make informed build-versus-buy decisions.
  • Mobilise and lead cross-functional teams, maintaining momentum where priorities, ownership, data or requirements are unclear.
  • Establish proportionate governance for delivery, AI security, responsible use, benefits tracking and value realisation.
  • Present clear recommendations, trade-offs and progress to investment partners, executive committees and senior operating leaders, building confidence and enabling timely decisions.

Qualifications

Required Skills

  • At least 10 years' experience operating across business strategy, technology and delivery, including leadership of enterprise data, AI or digital transformation programmes.
  • Strong executive stakeholder skills, with the credibility to influence investment partners, senior clients, technical leaders and delivery teams.
  • Able to simplify ambiguous business problems, isolate what matters and create enough clarity to move quickly without turning discovery into a prolonged strategy exercise.
  • Commercially minded, with experience connecting technology investment to financial or operational outcomes and tracking benefits through delivery.
  • AI fluent and pragmatic: understands capabilities, limitations and trade-offs well enough to shape a point of view, challenge assumptions and recognise when AI is not the answer.
  • Skilled in AI opportunity discovery, prioritisation, product strategy, roadmap development and workflow or operating-model redesign.
  • Sufficient technical depth to assess data readiness, architecture, integration patterns, scalability, operating cost, security and delivery risk.
  • Strong delivery leadership, including cross-functional team mobilisation, governance, dependency management and senior decision support.
  • Comfortable starting from zero and progressing without a fully defined problem, perfect data or an obvious delivery path.
  • Action oriented and evidence led, using focused tests, learning and iteration to deliver value quickly while protecting quality, scalability and responsible use.

 

Desirable Skills

  • Background in top-tier strategy or management consulting, AI or technology transformation, product leadership or innovation, supported by hands-on delivery experience.
  • Experience with generative and agentic AI, machine learning, predictive analytics, retrieval-augmented generation and enterprise knowledge systems.
  • Knowledge of data architecture and readiness, cloud AI platforms, enterprise integration patterns, AI governance, security and responsible AI practices.
  • Degree in engineering, computer science, data science, economics or another quantitative discipline; a relevant postgraduate qualification is desirable.
  • A demonstrable record of taking unclear opportunities from discussion to scalable delivery, making sensible trade-offs and achieving measurable business outcomes.

Skills Required

  • At least 10 years' experience across business strategy, technology and delivery, including leadership of enterprise data, AI or digital transformation programmes
  • Strong executive stakeholder skills with credibility to influence investment partners, senior clients, technical leaders and delivery teams
  • Ability to simplify ambiguous business problems, isolate what matters and create clarity quickly
  • Commercially minded: experience connecting technology investment to financial or operational outcomes and tracking benefits through delivery
  • AI fluent and pragmatic: understands capabilities, limitations and trade-offs to shape a point of view
  • Skilled in AI opportunity discovery, prioritisation, product strategy, roadmap development and workflow / operating-model redesign
  • Sufficient technical depth to assess data readiness, architecture, integration patterns, scalability, operating cost, security and delivery risk
  • Strong delivery leadership including cross-functional team mobilisation, governance, dependency management and senior decision support
  • Comfortable starting from zero and progressing without a fully defined problem, perfect data or obvious delivery path
  • Action oriented and evidence led, using focused tests, learning and iteration to deliver value quickly while protecting quality and responsible use
  • Background in top-tier strategy or management consulting, AI or technology transformation, product leadership or innovation with hands-on delivery experience
  • Experience with generative and agentic AI, machine learning, predictive analytics, retrieval-augmented generation and enterprise knowledge systems
  • Knowledge of data architecture and readiness, cloud AI platforms, enterprise integration patterns, AI governance, security and responsible AI practices
  • Degree in engineering, computer science, data science, economics or another quantitative discipline; relevant postgraduate desirable
  • Demonstrable record of taking unclear opportunities from discussion to scalable delivery achieving measurable business outcomes

Blend360 Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Blend360 and has not been reviewed or approved by Blend360.

  • Fair & Transparent Compensation Pay is considered fair-to-good by many, and public salary postings for common data roles indicate competitive packages in numerous markets. Feedback suggests overall company sentiment aligns with acceptable compensation relative to peers in consulting and analytics.
  • Flexible Benefits Flexible and remote/hybrid work arrangements are consistently highlighted in official materials and role descriptions. Feedback suggests flexibility is a meaningful part of the total rewards experience.
  • Retirement Support A 401(k) with company match is part of the core package. Feedback suggests retirement offerings are standard and contribute to a complete benefits set.

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The Company
HQ: Columbia, MD
390 Employees
Year Founded: 2016

What We Do

Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. Blend360 has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace.

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