At a Glance
- Tasks: Lead the delivery of custom AI solutions for enterprise clients in regulated industries.
- Company: Join a mission-driven tech company focused on safe and beneficial AI systems.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic role with travel opportunities and a focus on building innovative solutions.
- Why this job: Make a real impact by deploying cutting-edge AI technology in critical business processes.
- Qualifications: Experience in AI/ML deployments and strong stakeholder management skills required.
The predicted salary is between 63000 - 77000 £ per year.
About the company: the company’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the Role: As a Technical Deployment Lead on the Forward Deployed Engineering team, you will lead the delivery of custom AI agent solutions for enterprise customers in regulated industries. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes. You’ll own engagements end-to-end, from SOW through production deployment. You’ll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organizational complexity that comes with deploying AI agents in enterprise environments. You need to be technical enough to navigate architecture conversations with engineering stakeholders and polished enough to run executive briefings with C-suite sponsors. On top of that, you will help us to build playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world-class delivery, and bring insights back to our product and research teams on a regular basis.
Responsibilities:
- Own the technical delivery plan for each engagement.
- Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses.
- Translate customer business objectives into a sequenced roadmap that FDEs execute against.
- Lead discovery. Map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.
- Run day-to-day engineering execution. Drive delivery across the company and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path.
- Own product scoping for field engagements. Define the MVP, author requirements documentation, prioritise the engineering backlog, and manage scope against success criteria as requirements evolve.
- Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent the company's technical credibility with senior business and engineering leaders.
- Own value measurement and ROI. Define impact hypotheses, set baselines and KPIs, run pre- and post-deployment measurement, and report outcomes to executive sponsors.
- Codify reusable delivery assets. Build solution patterns, evaluation frameworks, and playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.
- Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organisational dynamics.
- Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and elevate with clear context when needed.
- Run delivery operations. Sprint ceremonies, milestone reviews, and progress reporting.
- Travel to customer sites. Build relationships, unblock delivery, and accelerate adoption (up to 25–50% travel expected).
You May Be a Good Fit If You:
- Have led AI/ML engagements/deployments, whether as a founder, data scientist, engineer, researcher, or in a professional services or consulting role.
- Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
- Have experience in a specialized vertical (life sciences, pharmaceutical, retail, mining, agriculture, etc.).
- Can navigate architecture discussions with engineering stakeholders, evaluate technical trade-offs, and pressure-test technical decisions. You won't write production code, but you will own the technical direction of engagements alongside FDEs.
- Have a track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making — ideally across multiple workstreams in regulated industries.
- Have executive presence — polished, credible, and comfortable representing the company to senior leaders in high-stakes environments.
- Thrive in ambiguity and bring structure where none exists.
- Have a builder's mindset — you're here to create a function, not just join one.
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ('OTE') range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £165,000—£230,000 GBP.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience. Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience. Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we’re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Technical Deployment Lead employer: United States Digital Space LLC
United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.
Contact Details:
United States Digital Space LLC Recruitment Team