Technical Deployment Lead
Anthropic is hiring a Technical Deployment Lead in London, United Kingdom. It pays £165k-£230k a year and Level rates it ; you can apply on Anthropic.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- Anthropic mentions visa sponsorship in this posting.
- Tools and skills the posting cites include AI safety, AI research and technical deployment.
- Level classifies it as a lead role.
- Level lists 680 other open roles at Anthropic.
AI in this role
Lead technical delivery of custom agentic AI solutions and deployment plans for enterprise customers at Anthropic.
About Anthropic
Anthropic’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 agentic AI solutions for enterprise customers. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes
Each engagement runs from SOW through production deployment. Forward Deployed Engineers build the technical solution; you drive the delivery plan, product scoping, stakeholder relationships, and the organizational complexity of deploying agents into complex enterprise environments.
You need to be credible in architecture conversations with engineering leads and equally comfortable running executive briefings with C-suite sponsors. You won't write production code, but you'll pressure-test technical decisions and make real-time trade-offs on scope and priority when things go sideways on an engagement.
This is also a builder's role. We're in the early innings of an emerging motion - the playbooks, the delivery patterns, the repeatable IP that makes the next engagement faster and better don't exist yet. The TDLs who thrive here are the ones who get that codifying what works is as important as the engagement in front of them right now.
Responsibilities
- Own the technical delivery plan for each engagement. Work from the signed SOW to a sequenced roadmap with clear milestones, dependencies, success criteria, and value hypotheses that FDEs execute against.
- Lead delivery discovery. Map customer workflows and constraints in depth, pressure-test the scoped MVP against what you find, and shape the solution architecture with the FDEs.
- Run day-to-day engineering execution. Drive delivery across Anthropic 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 during delivery. Author requirements, prioritize the engineering backlog, manage scope against success criteria, and hold the bar for what good looks like for the people and enterprises who will use the product.
- Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic'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.
- Contribute reusable delivery patterns. Capture what works on your engagements and feed field signal to the Programs Leads, Product, and Research.
- Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organizational dynamics.
- Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and escalate with clear context when needed.
- Run engagement-level delivery operations: sprint ceremonies, milestone reviews, and engagement reporting that feed the team's post-sales cadence and dashboards.
- 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.
- Operate like the CEO of your engagement. You take initiative without a mandate, make decisions with incomplete information, and lead rather than wait for instructions.
- 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 Anthropic 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 GBPLogistics
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.
We encourage you to apply even if you do not believe you meet every single qualification. 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.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
How we rate this
Technical Deployment Lead at Anthropic rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where technical deployment was part of your work. What did you do?
- Tell me about a project where product scoping was part of your work. What did you do?
- Tell me about a project where stakeholder management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Safety, AI Research, Technical Deployment, Product Scoping, and Stakeholder Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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