Forward Deployed Engineer

Reposted 2 Days Ago
Be an Early Applicant
2 Locations
Hybrid
180K-250K Annually
Senior level
Financial Services • Generative AI
Rational Dynamics builds customized AI reasoning systems for tasks of high cognitive complexity.
The Role
As a Forward Deployed Engineer, you will implement AI systems for clients by managing deployments, collaborating with researchers, and enhancing system design.
Summary Generated by Built In
The Company

Rational Dynamics builds customized AI reasoning systems for tasks of high cognitive complexity.

Our initial market is the world’s leading institutional asset owners. We work very closely with these customers to create specialized, rigorous benchmark datasets encompassing their most valuable and difficult knowledge work. Then we use the benchmarks to construct agentic large reasoning models, applying the same rigor to prove that the models correctly do the work. Customers access the models through a tailored application service, making their most skilled, expensive workers dramatically more productive.

We are an early-stage startup. Our founders previously started Voleon, now one of the world’s largest systematic investment managers, and recognized as a longstanding industry leader in applied machine learning. They bring to Rational Dynamics the same research discipline and data-driven focus that succeeded in the unforgiving, high-stakes setting of financial markets.

Job Opportunities

We are looking for entrepreneurial researchers and engineers who want to work on cutting-edge agentic AI methods and build out a best-in-class core technical infrastructure. Our work environment is highly collaborative. Your colleagues will be accomplished experts in AI/ML, statistics, and systems engineering.

Job Description

As a Forward Deployed Engineer, you'll build complete systems that solve real problems for institutional investors. You'll sit with customers to understand their workflows, then implement agentic AI systems that integrate with their proprietary data. This means building data pipelines, designing evaluation frameworks, and iterating on what's working in production.

You'll operate like a founder: take ownership, move fast, and figure it out. Whether that's jumping on a client call to understand risk workflows or writing an integration to connect data sources, you make it happen. You'll travel to customer sites, work alongside portfolio managers and analysts, and push solutions forward.

This role requires strong backend engineering combined with product thinking and customer empathy. You'll work with PhD researchers and a proven executive team solving problems that haven't been solved before. You need to be comfortable in ambiguity, technical enough to build production systems, and collaborative enough to translate customer needs into working solutions.

The right person thrives on customer interaction, builds backend systems from scratch, and wants to see their work impact billion-dollar decisions.

Duties
  • Collaborate with institutional investors and research scientists to understand requirements and pain points, then own end-to-end technical implementation of agentic AI systems from prototype to production, including deployment, monitoring, and customer-driven iteration

  • Ship code and documentation that meets the highest engineering standards for systems handling billion-dollar decisions

  • Drive continuous improvement of system design and deployment processes, identifying bottlenecks and scaling challenges before they become problems

Requirements
  • Relentlessness and customer focus, in large quantities

  • Demonstrable clarity of thought

  • 5+ years as a software engineer, preferably with a focus on backend systems and data infrastructure

  • Proven ability to ship production-grade applications in languages such as Python, Java, C++, Go, and Rust, and using agentic tools to modify customer frontends

  • Strong communication skills and ability to collaborate with diverse stakeholder groups, including non-technicians

  • B.A./B.S. in Computer Science or a related technical field

  • Willingness and enthusiasm for customer travel - this role requires on-site engagement to understand customer requirements and invent with customers

Preferred Qualifications
  • Experience building LLM systems and agentic workflows: RAG, tool use, multi-step reasoning, evaluation frameworks

  • Foundational AI/ML knowledge: You understand how modern generative AI works, even if you're not a researcher

  • Startup or founding experience: You've operated in ambiguity and built systems from scratch before

We expect that strong candidates won’t necessarily meet every qualification above. If most of this resonates and the gaps feel learnable, we’d rather hear from you than not.

“Friends of Rational Dynamics” Candidate Referral Program

If you have a great candidate in mind for this role and would like to have the potential to earn $7,500 to $15,000 if your referred candidate is successfully hired and employed by Rational Dynamics, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Rational Dynamics Referral Bonus Program.

 
Equal Opportunity Employer

Rational Dynamics is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Skills Required

  • 5+ years as a software engineer, preferably with a focus on backend systems and data infrastructure
  • Proven ability to ship production-grade applications in languages such as Python, Java, C++, Go, and Rust
  • Strong communication skills and ability to collaborate with diverse stakeholder groups, including non-technicians
  • B.A./B.S. in Computer Science or a related technical field
  • Willingness to go on-site for direct customer engagement
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The Company
7 Employees
Year Founded: 2025

What We Do

Our initial market is the world’s leading institutional asset owners. We work very closely with these customers to create specialized, rigorous benchmark datasets encompassing their most valuable and difficult knowledge work. Then we use the benchmarks to construct agentic large reasoning models, applying the same rigor to prove that the models correctly do the work. Customers access the models through a tailored application service, making their most skilled, expensive workers dramatically more productive.

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