Forward Deployed Engineer

Datasnipper; Hattem; On-site; EUR 90,000 - 130,000; Full time

Job summary

DataSnipper is seeking a Forward Deployed AI Engineer to embed with customers and build AI agents that automate audit and finance workflows. You will deliver from zero to live deployments, turning field learnings into product signal, and directly reducing manual effort in assurance work.

You will design and build agents, debug their accuracy in front of customers, and work with product and engineering to align deployments with customer needs.

Qualifications

• Hands-on, customer-facing role in a high-caliber team.
• Experience building with LLMs in practice: prompts, evaluating accuracy, debugging non-deterministic behavior.
• Familiarity with agent design patterns, evals, or AI observability.

Responsibilities

• Design and build agents; debug accuracy in front of customers.
• Assess feasibility of candidate agents and determine what is achievable.
• Produce robust agent configurations for real audit evidence.
• Mentor incoming FDE team members as the function scales.

Skills

AI agent design

LLM prompts

Customer-facing

AI observability

Documentation

Feasibility assessment

Tools

Claude

Job description

• We are looking for a Forward Deployed AI Engineer to join the Team at DataSnipper
• You will embed with our customers to build and refine the AI agents that automate their audit and finance workflows, taking them from zero to live in daily use and turning what you learn on the ground into the signal that shapes our product
• You sit at the exact point where our agent platform meets real assurance work, directly reducing manual effort and accelerating audit outcomes
• This is a hands-on, customer-facing role in a high-caliber team that moves fast and holds a high bar
• You will design and build agents, debug their accuracy in front of a customer, make the feasibility calls, and then make sure engineering hears what you saw
• The platform is still being shaped, so the role rewards people who are energized by building on something while making it better, not people who need fully stable tooling before they can deliver
• Build and earn the credibility with senior stakeholders like top-firm audit partners, engagement leaders, and methodology owners earning the credibility to influence how an entire practice adopts AI
• Design engagement programs that take a customer from zero to 20+ agents embedded directly into finance workflows and driving measurable impact
• Run office hours and resolve remaining issues, then hand off agent know-how cleanly to the Customer Success Manager who owns ongoing account health
• Build the more complex agents yourself, solving prompting and accuracy challenges against real audit evidence
• Assess the feasibility of candidate agents, and make the call on what is achievable within an engagement
• Produce robust agent configurations that anticipate edge cases and hold up under real customer use
• Operate a tight feedback loop between the customer and our product and engineering teams so issues and feature gaps reach the right people fast
• Surface gaps with enough specificity that they can be prioritized rather than lost and work closely with product and engineering on ideation and prioritization
• Foster documentation and knowledge sharing across delivery, product, engineering, and GTM teams
• Play a founding role in shaping DataSnipper’s professional services offering, translating early deployment learnings into repeatable frameworks, engagement models, and delivery standards as the FDE function grows
• Dedicate part of your time working directly with the product team to help design and develop new product capabilities, bringing the customer and deployment perspective into early-stage product thinking
• Mentor incoming FDE team members as the function scales, sharing domain knowledge, delivery instincts, and agent-building craft

• Technical literacy with data and documents, enough to configure them correctly and reason about what is going wrong
• The ability to do this in front of customers, under time pressure, without losing their confidence when something breaks
• Comfortable using a variety of AI tools like Claude in the build and test loop to move quickly
• Excellent written and verbal communication, including the ability to make a customer need legible to engineering
• Strong technical aptitude and structured thinking, with the judgment to decompose a customer workflow into agents and decide quickly what is feasible and what is not
• Bias toward shipping and iterating rather than perfecting in isolation, and willingness to travel to customer sites when an engagement calls for it
• Domain expertise in audit and/or finance or strong interest w/ ability to learn
• Hands-on experience building with LLMs in practice: writing and refining prompts, evaluating accuracy, and debugging non-deterministic behavior
• Familiarity with agent design patterns, evals, or AI observability
• Prior Forward Deployed Engineer, solutions engineering, or implementation experience at an applied AI or enterprise software company
• Experience with document processing and spreadsheet-heavy workflows