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Transformworks

Forward Deployed Engineer

Posted 7 Days Ago
Hybrid
New York, NY, USA
140K-200K Annually
Junior
Hybrid
New York, NY, USA
140K-200K Annually
Junior
Build end-to-end AI systems for clients including LLM integrations, workflow automation, data pipelines, and tooling. Ship production code, iterate on deployed systems, evaluate emerging AI tools, and contribute to internal engineering standards. Work closely with senior engineers and founders on architecture and client outcomes, with opportunity to lead engagements and grow quickly.
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About Transformworks

Transformworks is an AI implementation firm built for private equity. We partner with PE firms managing $10B+ in AUM to deploy AI across their portfolio companies in healthcare, education, and financial services.

We're profitable, growing fast (2x'd revenue in our most recent month), and doing it with a lean team that punches well above its weight. We own the full lifecycle from strategy through production deployment.

Our view is that AI has fundamentally changed what one great engineer with business judgment can accomplish. We're built around that. Rather than staffing large teams, we hire a small number of exceptional people, give them real ownership over client engagements, and pay them based on outcomes and speed. Compensation is uncapped and tied directly to the profit generated by the team.

The Role

You'll be building AI systems that go into production for real businesses. You'll work directly alongside the founding team and senior engineers on client engagements, owning pieces of the technical build from day one.

You'll learn fast here because you're close to everything: the client problem, the architecture decisions, the deployment, and the business outcome. You'll see how AI actually gets adopted inside companies and what makes the difference between a demo and something that changes how a business operates.

The best engineers here grow into leading engagements, owning client relationships, and building teams. That path moves quickly at a small firm growing fast, and the people who show up early have a fundamentally different trajectory.

What You'll Do
  • Build AI systems end-to-end: LLM integrations, workflow automation, data pipelines, and custom tooling

  • Ship production code for client engagements in healthcare, education, and financial services

  • Work with senior team members to translate business requirements into technical implementations

  • Iterate on deployed systems based on real-world performance and client feedback

  • Research and evaluate emerging AI tools against actual client needs

  • Contribute to internal engineering standards, tooling, and documentation as we scale

What We're Looking For
  • 1-3+ years of experience in software engineering or applied AI

  • Strong fundamentals in Python and comfort picking up new tools quickly

  • Some hands-on experience with LLMs, whether through work, side projects, or hackathons

  • You've shipped something real that people actually used

  • Bias toward figuring things out rather than waiting to be told what to do

  • Curious about the business side (you want to understand why you're building something, not just how)

  • Bonus: experience with RAG, agents, orchestration frameworks, or data pipelines

  • Bonus: exposure to healthcare, education, or professional services

What We Offer
  • The base salary range for this role is $140k to $200k, depending on experience, location, and level. In addition to base compensation, this role is eligible for profit-sharing and a comprehensive benefits package

  • Health, dental, and vision coverage for employees

  • Hands-on work with the latest AI models and tooling, applied to problems where the output matters to real operators and investors

  • Ownership of projects that move from strategy to production deployment

  • A small team where your work is visible, your judgment is trusted, and initiative is rewarded

  • Exposure to a wide variety of industries, tech stacks, and business problems, so no two weeks look the same

Based in New York or Philadelphia. This role follows a hybrid collaboration model.

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