Interested in this AI Consultant role at Version 1?
Apply Now →Skills & Technologies
About This Role
Company Description Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services.
We’re an award-winning employer reflecting how our employees are at the very heart of what we do:
- UK & Ireland's premier AWS, Microsoft & Oracle partner
- 4000+ strong, €450/£400m revenue business
- 10+ years as a Great Place to Work in Ireland & UK
- Best Workplace for Women in the UK & Ireland by GPTW
- Best Workplace for Wellbeing in the UK by GPTW
We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you!
Job Description AI is the biggest shift in how organisations build anend work in a generation. The organisations who win will be the ones who can move beyond a working demo and get genuinely production-grade, multi-agent AI systems live, reliable and maintained at scale. That is the hardest part of the journey, and it's where this role sits.
As an Applied AI Consultant, you bring that change to the top table. You've done this before — as a CTO, a founder, or the most senior engineering leader in your organisation — and you've taken a whole organisation through the shift to becoming AI native, not just a team. You are as comfortable setting direction with a Chief Executive or Chief Technology Officer as you are going deep on architecture with a lead engineer, and our largest, most strategic customers will look to you to set the pace of their AI transformation.
You'll shape and lead our most significant engagements, secure and hold executive sponsorship, and set the standard the rest of the team builds towards.
What You'll Do
- Own our most strategic engagements. Lead full-scale AI transformation programmes for our largest and most complex customers, from initial vision through to organisation-wide adoption.
- Set direction with the C-suite. Work directly with CEOs, CTOs, CIOs and other executive stakeholders to shape AI strategy, secure sponsorship, and connect adoption to the outcomes the business actually cares about.
- Transform whole organisations. Draw on your own experience taking an organisation through AI-native transformation to guide customers through the same shift — at the scale of a function, a division, or the whole business.
- Bring the vision. Act as a genuine AI visionary for our customers — someone who can see past the immediate ask to where the technology and the business are both heading, and bring customers with you.
- Shape how we sell and deliver. Help shape full transformation deals, define how value gets measured, and protect the trust our partners and customers place in Version 1.
- Lead and mentor. Set the standard for Applied AI Consultants, mentor senior hires, and help build the playbooks and IP that make the whole programme better.
- Represent Version 1 externally. Build our reputation and thought leadership in the market, as a visible, credible voice on AI adoption and transformation.
Qualifications What good looks like
- A proven AI transformation leader at organisation scale. You've personally led an organisation — not just a team — through becoming AI native, as a CTO, founder, or the most senior engineering leader in the room.
- Genuine AI vision. You don't just keep up with the field, you have a real point of view on where it's heading and what it means for how businesses operate — and people want to hear it.
- Fluent at C-suite level. You've operated as a peer to CEOs, CTOs and other executives, and you're just as comfortable setting strategy in the boardroom as you are getting hands-on with architecture.
- Deep technical credibility. Your AI engineering depth is real and current, not historical — engineers and architects trust your judgement because you've stayed close to the work.
- A track record customers can check. You can point to organisations you've genuinely transformed, and to the outcomes that resulted, not just initiatives you were involved in.
- Comfortable owning the outcome. You take full ownership of the largest, most ambiguous, highest-stakes engagements, and you bring the judgement and composure the moment needs.
What We're Looking For
- 10–15+ years in senior engineering leadership, as a CTO, founder, or the most senior technical leader in your organisation.
- Direct, personal experience leading an organisation-wide shift to becoming AI native, with outcomes you can speak to in detail.
- A genuine track record operating at C-suite level, comfortable setting direction alongside CEOs, CTOs and other executive stakeholders.
- Deep, current AI engineering expertise: production LLM and agent experience, evaluation frameworks, and deployment at scale.
- Experience shaping or building AI solutions and intelligent applications, not just overseeing them.
- Strong programming fundamentals and enough hands-on depth to be credible with architects and senior engineers.
- A degree in a related field, or equivalent practical experience.
Nice to have
- Experience as a founder or CTO of a business that itself went through AI-native transformation.
- A public profile — thought leadership, speaking, writing, or advisory work — in applied AI or AI transformation.
- Hands-on experience with the Claude API, Claude Code, MCP, or GitHub's AI tooling.
- Domain depth in a regulated or enterprise vertical: public sector, financial services, or healthcare and life sciences.
- Experience shaping large-scale commercial deals or outcome-based propositions.
Additional Information Why Version 1? At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability.
- Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits
- Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme
- Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance
- Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme
- Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies
- Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat
- Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform.
- Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes.
Version 1 is an equal opportunities employer.
We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring including those shaped by disability and neurodiversity.
Our employee-designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth.
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 9,079 AI roles we're tracking, AI Consultant positions make up 0% of the market. At Version 1, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Consultant roles pay a median of $156,360 based on 21 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Version 1 AI Hiring
Version 1 has 1 open AI role right now. They're hiring across AI Consultant. Based in London, England, UK.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Consultant roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.