Engineering Manager, Verticals – Financial Services

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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

Financial services is one of the most consequential domains for AI—and one of the most demanding. Workflows are complex, data is sensitive, regulatory expectations are real, and the people using these tools are experts who will immediately know if something doesn't work. That's exactly the kind of challenge we're here for.

Anthropic's Verticals team builds AI-powered products purpose-built for the industries where this complexity is highest. We're in early growth, moving fast, and earning the trust of enterprise customers who have seen a lot of vendors promise transformation and deliver demos. This role is about building something that actually changes how financial services teams work—and building the team that can do that sustainably.

We're looking for an Engineering Manager to lead the engineering work serving our financial services customers, with a near-term focus on deeply integrated experiences within Excel and PowerPoint. You'll own the people and execution of a team working on document-centric AI workflows—the kind that show up in investment banking, asset management, insurance, and corporate finance every day. Beyond your pod's work, you'll be a cross-vertical contributor, helping the broader Verticals team learn from what you're building and shape where we go next.

This is a high-ownership role at a company that's genuinely in a position to define what AI looks like in professional services for years to come.

Responsibilities

• Lead and develop a team of engineers building AI-powered experiences in Excel and PowerPoint for financial services enterprise customers
• Own engineering execution end-to-end: project planning, prioritization, delivery quality, team health, and incident response
• Partner closely with sales and customer success teams on enterprise deals—understanding customer requirements, participating in key conversations, and translating what you learn into engineering priorities
• Work with product and design to shape the roadmap, not just execute against it; you'll have a meaningful voice in what we build and why
• Maintain operational reliability on top of third-party platforms (the Microsoft 365 ecosystem), and build the processes that make your team resilient when those dependencies behave unexpectedly
• Engage with research and evaluation frameworks—developing intuition for model behavior, understanding evals, and helping the team make sound tradeoffs between capability and reliability
• Drive compliance and regulatory initiatives relevant to your customers, including owning the internal engineering work required to meet them
• Recruit, onboard, and develop strong engineers; give direct feedback, grow careers, and build a team culture that earns the confidence of enterprise customers

You may be a good fit if you

• Are a skilled engineering manager who takes the craft of management seriously: clear feedback, strong 1:1s, hard conversations handled well, and consistent investment in your team's growth
• Have experience building products for or within financial services—you understand how these organizations work, what they care about, and why trust and reliability aren't negotiable
• Know how to operate in an enterprise sales environment; you're comfortable alongside sales and customer success teams and can hold your own in customer conversations
• Have shipped AI-powered products and developed a grounded, practical understanding of what it takes to make them reliable and useful in high-stakes contexts
• Are experienced with the operational realities of building on third-party platforms—you've thought through degradation strategies, incident response, and the accountability gaps that come with dependencies you don't control
• Thrive in early-growth environments where the product is real but the playbook is still being written

Strong candidates may also have

• Deep domain knowledge in financial services—investment banking, asset management, insurance, corporate finance, or similar—whether from working within these institutions or building products for them
• Direct experience with compliance frameworks relevant to financial services and healthcare, and a track record of owning or driving compliance initiatives within an engineering organization; familiarity with HIPAA is a meaningful differentiator
• Experience managing teams that use AI-assisted coding tools, and a considered perspective on what that means for code review, quality standards, and engineering norms
• Exposure to both product-led growth and direct enterprise sales motions, with an understanding of how engineering decisions interact differently with each
• Vendor management experience—negotiating with, evaluating, or operationalizing third-party technology providers
• Familiarity with model evaluation frameworks and how evals can inform product decisions, not just research ones

Representative projects

• Partnering with an investment banking customer to understand their deal documentation workflow, then working with product to translate that into a concrete engineering roadmap
• Building an incident response and communication playbook for outages or degradation in Microsoft 365 integrations—and running the post-mortems that drive real improvements
• Owning a compliance initiative from scoping through delivery: working with legal and security, defining what engineering needs to build, and getting your team across the line
• Collaborating with research to design an evaluation framework that gives the team reliable signal on document generation quality across financial use cases
• Growing the team through a critical hiring period while maintaining velocity, quality standards, and the kind of culture enterprise customers can feel in their interactions with your engineers

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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:

$320,000—$485,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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