Tech Lead - Product Engineering

Basis equips accountants with a team of AI agents to take on real workflows.

We have hit product-market fit, have more demand than we can meet, and just raised $34m to scale at a speed that meets this moment.

Built in New York City. Read more about Basis here.

We're building product experiences where AI Accountants work as capable partners with humans, making complex accounting workflows simple, safe, and trustworthy.

LLMs put general intelligence inside software, which changes everything about how products work. We're designing completely new ways for humans and AI to work together. Just as mobile changed how we think about UI, AI requires new architectures, abstractions, and ways of thinking.

We work from first principles in small teams with quick feedback loops. We partner closely with Accounting SMEs, Design, PM, Research, and Platform. We think in systems, value clean abstractions and interfaces, and write code that's observable, maintainable, and easy for both humans and AI agents to work with.

As a Tech Lead on the Product Engineering team, you'll own the technical vision for a product surface or workflow: its architecture, quality, and evolution. You'll define how we build, teach others to build well, and ensure every product you touch is both robust and easy to understand.

Your focus is on technical clarity and architectural excellence: turning vague product ideas into clean, scalable systems that integrate smoothly with our ML stack. You'll lead by example through your code, reviews, and clear technical thinking.

You'll work with product managers, designers, and accountants to figure out what matters most, then lead the technical work to make it happen.

Own and evolve the product's technical architecture

• Define and own the architecture for your product area: APIs, clients, data flows, and observability.

• Make sure our systems are understandable: clean boundaries, explicit states, and predictable behavior.

• Run design and PR reviews that raise the bar for structure, performance, and maintainability.

• Make technical trade-offs clear and document your reasoning so decisions build on each other.

Ship products that integrate intelligence with precision

• Build interfaces and workflows that seamlessly blend human input and AI reasoning.

• Design APIs and services that connect product features with ML systems (retrieval, evaluations, context).

• Ensure systems are properly instrumented with telemetry, evaluations, and logging so success is measurable and problems are visible.

• Keep abstractions clean and AI-friendly: clear contracts, predictable state, no hidden behavior.

Lead through clarity and technical excellence

• Mentor engineers on design, code quality, and system thinking through specs, pairing, and reviews.

• Model clear technical writing. Every doc, PR, and review should help the team think better.

• Establish conventions that keep the codebase consistent and maintainable as we scale.

• Work with cross-functional teams to turn business needs into simple, testable technical plans.

📍 Location: NYC, Flatiron office. In-person team.

• 5+ years of full-stack or product engineering experience. We're open to exceptional candidates with different backgrounds.

• Strong foundations in API design, front-end systems, and reliable backend services.

• Practical experience integrating LLMs or ML capabilities into product workflows.

• Deep understanding of product architecture, data flows, and system design trade-offs.

• Proven ability to turn vague product goals into clean, iterative engineering plans.

• Excellent written and verbal communication. Your specs and PRs should be clear examples for others.

• Experience with TypeScript/React, Python, and Postgres.

• Familiarity with evaluation frameworks, telemetry, and instrumentation.

• Background in accounting, finance, or other workflow-heavy domains.

• Experience in fast-moving environments (startups or similar).

• A preference for simplicity, clarity, and understandable architectures.

• The systems you design are stable, extensible, and easy for others to understand.

• Engineers working with you learn to think more clearly and design better code.

• Product, ML, and platform systems align cleanly through your abstractions.

• You unblock others, raise quality standards, and speed up execution without creating bottlenecks.

• You work with clarity, conviction, and care, balancing quick iteration with solid craftsmanship.