Avatar for Togal.ai
Togal.ai
Actively Hiring
Construction Takeoff AI Software
  • Responds within three weeks
    Based on past data, Togal.ai usually responds to incoming applications within three weeks

Senior Product Engineer

  • $140k – $170k • No equity
  • |Remote ()
  • |6 years of exp
  • |Full Time
Posted: 4 days ago• Recruiter recently active
Hires remotely in
Remote Work Policy

Remote only

Visa Sponsorship

Not Available

Preferred Timezones
Alaska, Pacific Time, Mountain Time, Central Time, Eastern Time, Atlantic Time, Greenland
RelocationNot Allowed
Skills
Node.js
AI
TypeScript
React.js
Agentic AI

About the job

Location: Remote (US based)

About Us

Togal.ai is a cutting-edge AI research and development company specializing in computer vision and document understanding for the construction industry. Our mission is to transform how the world interprets construction drawings by extracting, clustering, and reasoning over the vector geometry hidden inside architectural PDFs.

Togal.AI is an AI-native organisation working at the intersection of AI, construction, and software craftsmanship, solving problems that save time, money, and human effort across pre-construction workflows. We are extending the classic full-stack seat with this role because we want people who discover, prototype, build, and deploy at AI velocity: better value delivered at many times the old speed, with accountability for the result.

This is a senior, high-autonomy role suited to someone who has shipped products with limited process and support. You’ll operate at the intersection of Product Management and Engineering: shaping what should be built and why, while also being capable of building, testing, iterating, and shipping production-quality software.

What you’ll do

  • Own intent and outcomes end-to-end. Take ambiguous customer problems, validate them through interviews, support data, product analytics, and market research, and drive them to shipped, verified value independently.
  • Discover with real users. Get close to how estimators and pre-construction teams actually work. Understand the problem before deciding what to build, and let user feedback steer what comes next.
  • Prototype as the argument. Build the working thing rather than the docs/deck. Use prototypes to test assumptions with customers, compare approaches, and decide what deserves production investment.
  • Build full-stack product experiences. Work across frontend, backend, APIs, databases, integrations, and deployment environments to take validated ideas into production.
  • Own the line between good and done. When AI agents write much of the implementation, you own product taste, scope, quality, and the decision about when to stop. Design the verification: tests, reviews, evaluations, user feedback, and monitoring that lets the team trust what ships without accumulating avoidable technical debt.
  • Move quickly through evidence-led iteration. Release improvements in small increments, learn from user feedback, and balance speed with reliability, quality, and customer trust.
  • Measure what ships and learn from the results. Track usage, customer feedback, conversion, retention, and reliability to understand what’s working, what isn’t, and where to invest next.
  • Respond to production issues. Diagnose root causes, and turn what you learn from customers and system behaviour into product improvements.

What you bring

  • Strong product judgement. You look past the stated request to find the underlying customer problem, challenge unclear requirements, and distinguish real opportunities from shiny distractions. You bring product sense, systems thinking, adaptability, and a clear sense of what a good product looks like.
  • Full-stack ability to ship production. Solid experience with TypeScript, Node.js, and a modern front-end framework (React, Next.js, or similar), comfort designing APIs, working with databases (SQL, Redis and similar), and deploying cloud services (AWS, GCP, or similar). You can take a feature from concept to production independently.
  • Fluency building with agents. You already use agentic coding agents to accelerate implementation while retaining ownership of architecture, security, correctness, testing, and production quality.
  • A verification mindset. You treat reviewing, testing, and evaluating agent-generated work as core to the job, and you own the difference between plausible and correct.
  • Ownership and high agency. You own outcomes, not tickets. You bring clarity to ambiguous problems, act without waiting to be told, and follow up to see whether what you shipped actually helped.
  • Clear communication. You are credible with customers, product, and engineers, and can drive group discussions and decisions.
  • Enterprise-grade quality. You ship and own production ready features, not POCs.

Why Togal?

  • Join a dynamic team of AI-native engineering team and from day one - you'll be building the quality discipline for a product that uses AI at its core, making every quality decision novel and impactful.
  • Be an advocate for quality at all times, not just a quality follower - this role has direct influence over how Togal defines and measures product excellence.
  • A culture of innovation, continuous learning, and high growth.
  • Comprehensive benefits, competitive compensation package and flexible work arrangements.

About the company

Togal.ai company logo

Togal.ai

Actively Hiring
Construction Takeoff AI Software51-200 Employees
Company Size
51-200
Company Industries
Artificial Intelligence / Machine Learning
  • Responds within three weeks
    Based on past data, Togal.ai usually responds to incoming applications within three weeks
Learn more about Togal.ai image

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