Engineering Manager, Agent Builder

DataSnipper•New York, NY

1d•Hybrid

About The Position

DataSnipper is hiring an Engineering Manager in its New York office to lead the Agent Builder team for Alwin, its agentic automation platform for audit and finance. The team owns the full lifecycle of agents, with firm-specific knowledge and context at its core. This includes capturing, curating, permissioning, and serving firms’ methodologies, guidance, templates, prior-year workpapers, and engagement context; enabling users to define agents; evaluating and approving them before publication; running and observing them on engagements; and governing, versioning, and retiring agents and knowledge. The Engineering Manager will set the team’s technical direction and lead through outcomes, building and developing a high-performing engineering team. The role requires balancing builder flexibility with reliable guardrails, and making evaluation, observability, traceability, approvals, and lifecycle management integral to the product. The manager will collaborate across Alwin with Agent Runtime, Evals, Document Intelligence, Product, Design, audit methodology experts, and customer-facing teams to turn enterprise rollout learnings into platform capabilities. The role also helps shape how DataSnipper engineering uses AI-assisted development. DataSnipper builds AI solutions for audit and finance professionals, emphasizing outputs that are explainable and traceable to their sources. Its Alwin platform processes documents in the cloud and provides an audit trail. DataSnipper reports serving more than 600,000 professionals across 3,000+ organizations in 175 countries. The company is backed by a $100 million Series B led by Index Ventures and is a member of 1% for the Planet. The position is hybrid, with at least three days onsite each week in the New York City office. The company describes an international team across five global offices.

Requirements

At least 3 years of experience leading engineering teams, in addition to at least 5 years as a software engineer.
An empowerment-oriented leadership style and a track record of hiring and building high-performing teams.
Hands-on experience with agentic or LLM systems in production, including context engineering and retrieval; understanding of control loops, tool calling, grounding, and evaluation sufficient to challenge technical designs.
Experience building platform products with a lifecycle, including versioning, permissions, release, and deprecation for customer-built artifacts.
Strong fundamentals in software architecture, distributed systems, APIs, and cloud-native development.
Strong product aptitude, including challenging problem framing, making roadmap trade-offs, and focusing on customer success.
Hands-on fluency with AI coding tools and agentic harnesses, and experience improving a team’s effectiveness through their use.
Comfort leading across time zones and offices, with clear written communication.

Nice To Haves

Knowledge management or enterprise search experience, including ingestion, chunking, embeddings, hybrid retrieval, document-level permissions, and content freshness.
Experience with knowledge graphs or structured representations of policies, procedures, and rules.
Experience building low-code or configuration products, workflow designers, rule engines, or domain-specific languages.
Practical agent evaluation experience, including datasets, offline and online experiments, failure classification, and measuring context’s impact on quality.
Experience in regulated domains such as audit, financial services, or healthcare, where traceability, approvals, and access control are requirements.
Experience managing governance at scale across enterprise customers, teams, and thousands of users.
Experience with Python, Azure, and observability tooling.
Domain experience in audit methodology, accounting, or fintech.

Responsibilities

Lead the Agent Builder team through clear goals and outcomes, trusting the team to determine how to deliver them.
Hire, grow, and retain senior engineers in New York, and improve the team’s capabilities over time.
Own Agent Builder’s end-to-end technical direction while staying close enough to the code to make credible technical decisions.
Build the knowledge and context layer that grounds agents in firm-specific methodology, including how knowledge is captured, maintained, permissioned, retrieved, and evaluated for impact.
Set the right balance between builder flexibility and guardrails so agents can represent real methodologies while remaining dependable.
Design agent lifecycle capabilities, including versioning, approvals, rollout, and sunsetting.
Make agent evaluation, observability, and auditability core product capabilities.
Partner with Agent Runtime, Evals, Document Intelligence, Product, Design, audit methodology experts, Forward Deployed Engineers, Solution Architects, and GTM teams to deliver a coherent platform and turn enterprise rollout learnings into platform capabilities.
Set a high bar for AI-assisted engineering and shape how DataSnipper engineering uses AI.

Benefits

Equity in the form of Stock Appreciation Rights.
Flexible paid time off.
Comprehensive medical and dental coverage.
401K match.
Paid parental leave.
Company-sponsored lunch.
Hybrid work, with at least three days onsite each week in the New York City office.
Continuous learning and development initiatives.
Access to a mental health and wellness platform.
Social and team-building activities, including company-wide events.