Manager, Technical Deployment (Financial Services)
Anthropic · New York City, NY ·
- Category
- Management
- Experience
- 3+ years
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
Anthropic is building the Forward Deployed Engineering team to help the world's most ambitious organizations adopt Claude in ways that are transformative, safe, and lasting. Our Technical Deployment Leads (TDLs) and Forward Deployed Engineers (FDEs) embed with strategic customers to ship production AI applications that solve real business problems. Our delivery model pairs two roles: FDEs own the technical artifact, and TDLs own the engagement end-to-end — from statement of work (SOW) through production deployment.
As a Manager of Technical Deployment for Financial Services, you own engagement portfolio health across your vertical. You set the bar for delivery quality and build the playbooks and evaluation frameworks that let the practice scale. Your work will directly influence Anthropic's product direction and establish Anthropic as the trusted partner for AI transformation across the Fortune 100.
This is a player-coach role. You need to be credible in architecture conversations with a customer's engineering leads and equally comfortable in sales conversations in front of executive sponsors, and you will lead the most complex engagements yourself when the stakes call for it. Most of your impact will come through the people you hire and the standard you hold them to. You won't write production code, but you will pressure-test the technical decisions your TDL team makes with FDEs.
Responsibilities
- Hire, develop, and retain a team of TDLs embedded in Financial Services engagements. Set a high bar for delivery judgment, technical fluency, and customer presence, and run the interviews that hold it.
- Manage each TDL directly: regular 1:1s, clear expectations, direct feedback, and a growth plan. Build a bench that runs engagements well without you in the room.
- Own portfolio health across the vertical. Track which engagements are on track, at risk, or closing out, and intervene early when delivery drifts. Run engagement quality reviews with your team.
- Own customer outcomes across the portfolio. Hold the executive relationship with customer sponsors, run steering committees, and represent Anthropic's credibility with senior business, risk, and engineering leaders.
- Make the staffing call for each engagement. Work with FDE managers to match TDLs and engineers to each customer, and adjust as scope changes.
- Lead the most complex engagements yourself. Take the TDL seat when engagement size, regulatory exposure, or organizational complexity calls for it, from delivery plan through production.
- Set the bar for delivery excellence — SOW quality, MVP scoping, and value measurement. Ensure every engagement has a defensible impact story.
- Codify reusable solution patterns, evaluation frameworks, and technical playbooks across the team. Turn what works in the field into delivery infrastructure that lets the practice scale.
- Partner with Sales to qualify engagements, shape scope, and inform SOWs. Partner with Marketing and Sales on Financial Services–specific go-to-market materials, reference cases, and positioning.
- Run the team's operating rhythm: engagement reviews, knowledge-sharing, and escalation support, and report into the wider post-sales cadence and dashboards. Set team goals tied to customer outcomes.
- Bring the field back to Anthropic. Surface delivery lessons and emerging Financial Services use cases to Product and Research, and represent the vertical in leadership discussions.
- Consistently uphold Anthropic's values as you lead your team. TDLs should be strong representatives of Anthropic's culture as they work within customer environments.
- Travel to customer sites (25–50% expected).
You May Be a Good Fit If You
- Have 8+ years leading enterprise AI/ML delivery, whether you came up as a founder, engineer, data scientist, or researcher who has moved into deployments, with at least 3 years directly managing people who owned delivery outcomes.
- Have a track record of building and leading technical delivery teams in enterprise environments, ideally including embedded or forward-deployed teams working at client sites.
- Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
- Bring depth in Financial Services. You have delivered technology programs inside banks, insurers, or asset managers, you understand how model risk, security, and compliance review shape what ships, and you can speak credibly with a CIO, a chief risk officer, and a head of engineering.
- Can navigate architecture discussions with engineering stakeholders, evaluate technical trade-offs, and judge whether a proposed agent design is realistic. You are accountable for the technical direction your team sets alongside FDEs.
- Have experience with value-based scoping, including TCO/ROI quantification and post-deployment impact measurement.
- Thrive in ambiguity and bring structure where none exists. You have built a team, practice, or function from an early stage.
- Have executive presence: polished, credible, and concise with senior leaders in high-stakes settings, and just as effective in a hands-on engagement review with your team.
- Have strong written and verbal communication skills. You can translate technical complexity into clear narratives for diverse audiences.
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.
Logistics
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 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.