Ai Engagement Lead

Whitesmith; Braga; On-site; EUR 47,000 - 56,000; Full time

Job summary

Whitesmith, an AI-first technical partner, is hiring an AI Engagement Lead to own client accounts and lead AI implementation programmes from discovery to renewal. You will work with leadership and a small team of Forward Deployed Engineers to drive adoption, measurable outcomes and growth.

Travel for discovery and workshops is expected. You bring strategic, technical depth and commercial judgment to shape engagements, leaving behind reusable playbooks and strong client relationships.

Qualifications

• Experience leading complex client engagements end-to-end.
• Proven ability to drive AI delivery and organizational change.
• Strong communication with senior stakeholders and sponsorship teams.
• Background in consulting, professional services or forward-deployed delivery.

Responsibilities

• Own client accounts from discovery through delivery, adoption, renewal and growth.
• Lead AI implementation programmes with a small embedded engineering team.
• Turn executive ambitions into measurable outcomes with a clear delivery plan.
• Build trusted relationships with sponsors and client teams, guiding priorities and decisions.
• Identify opportunities for renewal and paid expansion based on client impact.

Skills

Client leadership

AI delivery

Stakeholder management

Project management

Team leadership

Job description

€47,000 to €56,000 gross annual salary, plus an annual benefits budget of €21,000 to €24,000, including meal allowance. Total annual package: €68,000 to €80,000. Profit sharing: in addition to salary and benefits, we share company profits with the team, equivalent to around 8% of annual gross salary on average. Final payouts depend on company results and the scheme's allocation rules. Travel:

Occasional client travel, typically for discovery, kick-offs and important working sessions Whitesmith is an AI-first technical partner with deep roots in senior software engineering. We help established organisations make AI part of how their teams actually work: not a slide deck or an isolated proof of concept, but a working operating model with useful systems, trained people and measurable outcomes. We are hiring an AI Engagement Lead who wants to learn how to solve hard problems together with clients and a small technical team.

You do not need to arrive with every answer; you do need to take ownership of finding a responsible path forward. You will own a portfolio of client accounts, working directly with leadership teams and a small embedded team of one or two Forward Deployed Engineers. You will lead AI implementation programmes, accountable from discovery and scoping through delivery, adoption, renewal and growth. Portfolio size will reflect the work each client buys, delivery intensity and the capacity needed to sustain an excellent client experience.

This is an outcome-owning client leadership role. You bring the product and technical depth to challenge a plan, strong commercial judgment to develop and grow the engagement, and exceptional relationship-building skills with senior stakeholders to move an organisation through change. What you will own

What you will own

The client outcome.

Turn an executive ambition or messy operating problem into a small number of outcomes, a delivery plan and clear evidence of progress. Keep the work tied to real adoption and business impact. The client relationship and experience.

The client relationship and experience.

Become a trusted partner to sponsors and the people doing the work. Anticipate priorities, challenge constructively and help the organisation make better decisions. Build confidence through direct human contact, visible progress and effective recovery when things change. The team.

The team.

Give one or two FDEs context, priorities and fast decisions. Remove blockers and protect their time without standing between them and the users. Hold a high quality bar without micromanaging the craft. Account strategy and growth.

Account strategy and growth.

Continually identify unmet needs and opportunities that matter to the client. Turn insight and demonstrated impact into a forward account plan, renewal and paid expansion. Own the business case, scope and account economics; growth should improve client outcomes and Whitesmith's long-term value. AI-native delivery.

AI-native delivery.

Use AI as part of your own operating system for research, analysis, planning, communication, quality checks and knowledge capture. Decide what to delegate to AI, what needs human judgment and how to verify the result. Help the client develop the same judgment. The playbook.

The playbook.

Turn field learning into reusable skills, templates, evaluation methods and delivery patterns. Each account should make the next one better. What good looks like after six months

What good looks like after six months

Client accounts run under clear Lead accountability, without routine dependence on company leadership. Leadership joins monthly strategic planning and handles exceptional escalations. Any closer support during handover is temporary. Client sponsors can name the outcomes, evidence and next decisions without needing a presentation translated for them. FDEs have clear priorities, fast escalation paths and enough direct access to users to ship useful work. Scope, burn and margin are visible.

Changes are handled before they become surprises.

AI-enabled workflows are in production or regular use, with adoption and quality measured rather than assumed. Lessons from each engagement have become reusable Whitesmith IP. Account growth is evidenced by an agreed renewal or paid expansion addressing a validated client need, with explicit outcomes, scope and healthy economics, not free additional delivery. You may be a fit if

You may be a fit if

You have owned complex client work from start to finish in consulting, professional services, product delivery, change programmes or a forward-deployed environment. You have led small, senior technical teams through ambiguous work and can show what changed because of your decisions. You can earn trust in an enterprise boardroom, work directly with senior leadership and remain useful to the people delivering the work.

You can move from a technical deep-dive to a board-level presentation in the same afternoon, connecting the engineering decisions to business outcomes, adoption and commercial trade-offs. You can show how your own initiative strengthened a client relationship and developed valuable follow-on work. You use current AI tools deeply in your own work. You can show workflows you designed, where the model was wrong, how you checked it and what you changed. You write and speak clearly.

You build trust through direct conversation with clients, by phone, video or in person, and make difficult situations easier to understand. You take ownership when the path is unclear: make assumptions explicit, choose a responsible next step and seek help without handing off the result. You do not need a particular degree, a pedigree consultancy or one named AI product.

Bring the technical and client-delivery capability this role requires; we value demonstrated motivation, follow-through and collaborative learning over having the quickest answer. This role is probably not for you if

This role is probably not for you if

You prefer to coordinate specialists without being accountable for their outcome. Your client style is to agree in the room and negotiate with the team afterwards. Your AI practice is mostly prompting for polished first drafts. You treat adoption, data quality, evaluation, privacy or security as someone else's problem. You need a complete brief before you can create momentum. How we hire and how AI fits

How we hire and how AI fits

AI is part of the job, so it is part of the selection process. Some stages explicitly ask you to use it and show us how you work. Other live conversations are AI-free because we need to understand your own judgment. We tell you which is which in advance. We reward transparent, sophisticated AI use: framing, deliberate context, delegation, verification and ownership, not secret assistance or polish detached from experience. Expect to attempt a problem, receive feedback and improve your approach.

We assess how you learn and act, not whether you already know every answer. Our six stages are:

• a five-minute demo
• short recorded answers
• a live structured screen
• a practical exercise with reference checks in parallel
• an in-person discovery and team session
• and a final decision

We aim to respond within two working days after each stage and complete the process in about three to four weeks. If delayed, we will explain why and give a revised decision date.

Whitesmith is an equal-opportunity employer. We welcome applicants with different backgrounds and will provide reasonable adjustments throughout the process. If an assessment constraint conflicts with an accessibility need, tell us and we will agree an equivalent way to demonstrate the skill. Where's your next real AI gain?

A short check reads where your organisation's AI momentum is building, where it's stalling, and the moves that matter most next.