Description
Come build the future of finance with Datarails. We're a global, AI-powered FinanceOS company helping finance teams transform the way they work. By combining intelligent automation, AI, and seamless integrations with the tools finance teams already know and trust, we empower organizations to make faster, smarter decisions with confidence. With approximately 350 employees worldwide, we're building the next generation of finance technology - where innovation, collaboration, and customer success go hand in hand.
If you're looking for a fantastic opportunity to join a growing startup in a role with massive impact, we would love to meet you!
This position is 100% remote, based anywhere in the United States. No sponsorship or relocation assistance is available.
About The Role
We are hiring for two focus areas on this team. This posting is for the Applied AI focus. If you are stronger in deployment, infrastructure and platform engineering, see the Platform focus posting for the same role.
As a Forward Deployed Financial Engineer, you will lead the discovery and delivery of Datarails' AI transformation engagements for existing customers.
After a customer completes implementation, you will work closely with their team to understand how they operate, identify where AI can create meaningful value, and determine what Datarails can build with them. You will develop a comprehensive recommendation and then take an active role in bringing that vision to life.
The solutions may include AI skills, routines, applications, agents, or workflows. This is a highly hands-on role for someone who enjoys working directly with customers, navigating ambiguity, and building practical solutions that solve real business problems.
In the Applied AI focus, you are the engineer who takes on the engagements where the AI itself is the hard part: agents that reason over financial data, systems that chain steps and check their own work, and applications that put those systems in front of a finance team. You set the bar for how the team builds and evaluates AI systems.
You will also serve as an important bridge between customers and our R&D and Product teams, helping translate customer needs into scalable capabilities and influencing the future of the Datarails platform.
What You’ll Do
- Help customers answer: What do we need, and how can we build it together?
- Lead discovery sessions with customers to understand their processes, challenges, goals, and AI transformation opportunities.
- Develop comprehensive recommendations and solution plans for customer AI transformation projects.
- Design, build and ship customer-facing solutions, including AI agents, skills, routines, workflows and applications, on top of Datarails, Claude and the customer's connected systems.
- Define how the solutions you build are tested and evaluated, so the team knows they work before a customer relies on them.
- Take ownership of projects from initial discovery and recommendation through development and delivery.
- Work directly with customers throughout the engagement, translating business requirements into practical technical solutions.
- Engage customers in change management, helping usher their teams into a more AI-native way of working.
- Build prototypes and products that address immediate customer needs while identifying opportunities for broader reuse.
- Partner closely with Datarails Customer Success, Product and R&D teams to troubleshoot challenges, communicate customer requirements, and influence product development.
- Identify recurring customer needs that could evolve into scalable platform capabilities.
- Clearly explain technical concepts, tradeoffs, and recommendations to both technical and non-technical stakeholders.
- Document solutions, learnings, and repeatable approaches that can improve future customer engagements.
What We’re Looking For
Two things come first, whatever the focus:
- You are good in front of the customer. You can run discovery with a finance team, explain a tradeoff to a controller, and hold the room when the plan changes. Half of this job is that.
- You ship. You own a problem from the first conversation through to a working solution the customer actually uses.
Then three technical areas, weighted in this order for the Applied AI focus:
- Applied AI. You have built and shipped LLM-based systems for real users: agents, tool use, retrieval, prompt and context design, evaluation. You know where these systems break and how to make them dependable.
- Marry the Business Value with the AI Use Case. You understand and continue growing in the business domain so you can bridge the AI solution with what matters to the customer
- Deployment. You can get what you build running somewhere other than your laptop: APIs and integrations, a cloud environment, authentication.
Also:
- Production experience in Python or TypeScript, with SQL and REST APIs.
- Hands-on experience with modern LLM tooling: agent frameworks, Model Context Protocol, tool use, evals.
- Impact obsessed: driven to deliver measurable outcomes for the customer, and to capture and market those results forward.
- Ability to translate ambiguous business challenges into clear technical recommendations.
- A product-oriented mindset and system-level thinking, with an interest in building solutions that may evolve beyond a single customer use case.
- Comfort working independently, managing projects, and taking ownership from discovery through delivery.
- Ability to collaborate effectively with Product, R&D, Customer Success, and other cross-functional teams.
- Curiosity, adaptability, and a willingness to experiment, learn quickly, and solve problems creatively.
Helpful Experience
- Forward deployed engineering, hands-on technical consulting, or early engineering roles with broad implementation responsibility.
- Applied AI or ML engineering: you built AI features into a product and want to work directly with the customers who use them.
- Finance, accounting, FP&A, Excel-based workflows, or integrations with ERP and other business systems. You will learn the Office of the CFO quickly here; you do not need to arrive from it.
What We Offer
- A collaborative, team-oriented environment, the ability to own your own schedule (work your local time zone), and the opportunity to grow at Datarails over many years
- Base compensation - The target base salary range will be between $120-150k USD per year, based on multiple factors including prior experience, skills, and location. We are open to candidates with varying levels of experience.
- Parental leave
- Meaningful equity
- 401(k) plan with up to 4% match
- Top-of-the-line healthcare (medical, vision, and dental), with 100% paid coverage for employees + generous coverage for dependents
- Generous PTO + 12 paid company holidays
- Life insurance
- And more!
We want to make sure everyone has an equal chance to participate and make a difference. Datarails is an equal opportunity employer and prioritizes building a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants of any type and do not discriminate based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state, and local laws. Datarails’ policy is to comply with all applicable laws related to nondiscrimination and equal opportunity and will not tolerate discrimination or harassment based on any of these characteristics. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
Skills Required
- Production experience with Python or TypeScript
- Experience with SQL and REST APIs
- Hands-on experience building and shipping LLM-based systems for real users
- Experience with AI agents, tool use, retrieval, prompt and context design, and evaluation
- Hands-on experience with modern LLM tooling, agent frameworks, Model Context Protocol, tool use, and evaluations
- Ability to deploy solutions using APIs, integrations, a cloud environment, and authentication
- Ability to lead customer discovery and explain technical tradeoffs to technical and non-technical stakeholders
- Ability to translate ambiguous business challenges into clear technical recommendations
- Ability to own projects from discovery and recommendation through development and delivery
- Product-oriented mindset and system-level thinking
- Ability to collaborate with Product, R&D, Customer Success, and cross-functional teams
- Curiosity, adaptability, willingness to experiment, and creative problem-solving
- Experience with forward deployed engineering, technical consulting, or broad implementation responsibility
- Applied AI or machine learning engineering experience building AI features into products
- Experience with finance, accounting, FP&A, Excel-based workflows, ERP, or other business-system integrations
Datarails Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Datarails and has not been reviewed or approved by Datarails.
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Fair & Transparent Compensation — Compensation is widely characterized as competitive and well‑regarded, contributing to strong satisfaction with total pay. Feedback suggests pay levels are seen as market‑appropriate and a core strength of the employment offer.
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Healthcare Strength — Benefits descriptions indicate employer‑paid medical, dental, and vision for employees, with company contributions for dependents. Feedback suggests health coverage is a standout element of the package.
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Leave & Time Off Breadth — Time‑off policies are described as flexible, including unlimited PTO with guidance on expected usage and paid company holidays. Feedback suggests employees also reference ample vacation allowances and the ability to carry time forward in some cases.
Datarails Insights
What We Do
Datarails has created a solution that tackles one of the biggest challenges in financial departments: the overflowing amount of data that, up until now, was managed by tons of Excel sheets. All those financial reports, forecasts, expenses, analytics? Datarails takes all this data and integrates it into a one, simple, smart report. Datarails consolidates all cross-organizational data and enables finance professionals to follow it, manage it, and derive insights from analysis. Instead of spending time on manual consolidation, Datarails automates the consolidation process and the creation of financial reports. It’s cloud-based, so nothing gets lost, it’s brilliant, so almost every feature can be added.
Why Work With Us
We're on a mission to transform finance. Datarails is committed to a positive, diverse, and inclusive culture by hiring for potential, focused on the inclusion of people who have different ways of thinking, different viewpoints, different backgrounds, and different skill sets. We value a transparent and open culture that positively impacts our team
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