Forward Deployed Financial Engineer - Applied AI
About this role
Engineers who thrive in front of customers, enjoy navigating ambiguity, and take pride in shipping practical solutions that solve real business problems will find a natural home here. Datarails operates a global FinanceOS platform that combines intelligent automation and artificial intelligence to help finance teams transform their daily workflows.
As a Forward Deployed Financial Engineer focused on Applied AI, the person in this role will lead discovery sessions with existing customers, uncover operational challenges, and design custom AI transformations. Working directly with clients, the engineer will build and evaluate systems where the AI is the core challenge, including autonomous agents, multi-step reasoning workflows, and user-facing applications built on top of modern language models and connected business systems.
Operating as a vital technical bridge between end-users and internal R&D teams, the successful candidate will translate complex business requirements into scalable platform capabilities. The position suits adaptable, impact-driven builders who possess both client-facing communication skills and hands-on technical expertise in deploying dependable language model architectures.
What you will do
- Lead discovery sessions with customers to understand their operational processes, challenges, goals, and AI transformation opportunities.
- Design, build, and ship customer-facing AI agents, skills, routines, workflows, and applications using Datarails, Claude, and connected systems.
- Define and execute testing and evaluation protocols to ensure reliability before customers rely on deployed solutions.
- Take end-to-end ownership of projects ranging from initial discovery and strategic recommendations through development and delivery.
- Engage customers in change management to help usher their teams into an AI-native way of working.
- Partner closely with Customer Success, Product, and R&D teams to troubleshoot challenges and influence product development.
- Document solutions, learnings, and repeatable approaches to improve future customer engagements.
What you need
- Demonstrated ability to run discovery with finance teams, explain technical tradeoffs, and hold the room when plans change.
- Production experience building and shipping LLM-based systems for real users, including agents, tool use, retrieval, and evaluation.
- Practical experience deploying applications beyond a local environment, involving APIs, integrations, cloud environments, and authentication.
- Production experience in Python or TypeScript, accompanied by proficiency with SQL and REST APIs.
- Hands-on experience with modern LLM tooling such as agent frameworks, Model Context Protocol, and tool use.
- Ability to translate ambiguous business challenges into clear technical recommendations and measurable customer outcomes.
Nice to have
- Forward deployed engineering, hands-on technical consulting, or early engineering roles with broad implementation responsibility
- Applied AI or ML engineering experience building features directly for end users
- Familiarity with finance, accounting, FP&A, Excel-based workflows, or integrations with ERP and other business systems
Benefits
- Parental leave
- Meaningful equity
- 401(k) plan with up to 4% match
- Top-of-the-line healthcare including medical, vision, and dental with 100% paid coverage for employees
- Generous PTO plus 12 paid company holidays
- Life insurance
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The position is 100% remote and based anywhere in the United States. Employees are able to own their own schedule by working in their local time zone.
What is the salary range for the role?
The target base salary range is between $120,000 and $150,000 USD per year. Actual compensation is determined by multiple factors including prior experience, skills, and location.
Is visa sponsorship or relocation assistance available?
No sponsorship or relocation assistance is available for this position. Candidates must be authorized to work in the United States.
What core technical skills are required?
The role requires production experience in Python or TypeScript, along with SQL and REST APIs. Candidates also need hands-on experience building and shipping LLM-based systems such as agents, tool use, retrieval, and evaluation.