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What we're looking for
- 5+ years experience in customer-facing AI or agentic systems roles
- Experience in forward-deployed engineering or solutions engineering at an AI-first company
- Experience in applied AI / ML engineering with direct customer exposure
- Technical consulting on AI or automation projects
- Fluency in operational domains like supply chain, procurement, or finance ops
About the role
About the role
FDEs are how we bring AI to life inside our customers. You sit at the front line, map their workflows on the platform, improve the underlying processes, and turn the result into running agents that deliver tangible business impact. Scoping, build, debug, handover, expansion. You own the customer outcome end to end — and the relationship that goes with it.
You won't write the core product. You will write the glue: integration scripts, agent configurations, data transformations, prototypes — whatever it takes to get an agent running against a customer's actual systems. You'll spend real time inside their stack and inside their team.
If you like the messy middle between AI, process, and customer, this is the role.
What you'll do
Embed with customers from kickoff through go-live and beyond
Map customer workflows directly on the platform and decide what's worth automating, what's worth fixing first, and what's blocked
Improve the underlying processes where it matters — don't automate broken flows, redesign them
Translate business logic into agent behaviour: actions, decision rules, exception paths, fallbacks
Configure and ship agents against real customer systems (ERPs, portals, spreadsheets, email, custom tools)
Write integration code, scripts, and prototypes when the situation calls for it
Debug live agents in production and iterate quickly
Build and own the working relationship with customer stakeholders, from operators to sponsors
Run working sessions, hold your own with technical counterparts, and earn the right to push back
Capture reusable patterns, templates, and runbooks so the next deployment is faster
Send recurring workflow patterns back to Product and Engineering as real signal
What success looks like
Multiple agents in production across clients, with measurable business impact
Customers point to specific KPIs that moved because of your work
Customers treat you as a trusted operator and want you in the room
Process improvements you drove are visible in the customer's day-to-day, not just in the agent
Accounts you own expand because the relationship and the results are both there
Each deployment is faster than the last because you've left behind reusable assets
Experience
5+ years in roles where you've shipped against real customer environments. We're prioritising AI-native candidates: people who have been building, deploying, or operating AI and agentic systems in customer-facing settings, not adjacent to them.
Likely backgrounds: forward-deployed or solutions engineering at an AI-first company · applied AI/ML engineering with direct customer exposure · technical consulting on AI or automation where you owned delivery and the client relationship · operations or product roles where you've built and shipped AI-powered tooling against messy real-world systems.
Retail, e-commerce, or CPG background is a strong plus. Fluency in any operational domain — supply chain, procurement, category management, merchandising, finance ops, supplier management, warehousing — helps you ramp faster. What matters most is that you can pick up a new business quickly, see how to improve it, and build something with AI that actually works.
Skills
Hands-on with modern AI tooling: LLMs, agent frameworks, prompt engineering, evals, MCP, retrieval · strong systems thinking and engineering judgment · process design instinct · comfortable in code-adjacent territory: SQL, Python or JS scripting, APIs, JSON, webhooks · familiarity with ERPs and enterprise stacks is a plus · able to lead a working session, manage a stakeholder, push back on bad scope, and explain trade-offs without hiding behind jargon · fluent English; additional European languages are a plus.
Mindset
Bias to ship. Comfortable with ambiguity, half-built systems, and changing requirements. Low ego, high standards. Customer-obsessed — you build trust by being useful, not by being polished. Commercially aware. Honest about what's working and what isn't.
What we offer
A small, sharp team that values ownership and candour
Real product and culture leverage from day one
Customer-facing impact: your work ships and moves the business
Competitive comp including equity · option to trade cash for equity
How we hire
Online screen
Hiring manager interview (remote or on-site)
Case study and presentation
Founder interview
We're not looking for perfection. We're looking for someone who can walk into a customer's operation, figure out what matters, fix the process, ship the agent, and turn AI into outcomes the business can feel.
FDEs are how we bring AI to life inside our customers. You sit at the front line, map their workflows on the platform, improve the underlying processes, and turn the result into running agents that deliver tangible business impact. Scoping, build, debug, handover, expansion. You own the customer outcome end to end — and the relationship that goes with it.
You won't write the core product. You will write the glue: integration scripts, agent configurations, data transformations, prototypes — whatever it takes to get an agent running against a customer's actual systems. You'll spend real time inside their stack and inside their team.
If you like the messy middle between AI, process, and customer, this is the role.
What you'll do
Embed with customers from kickoff through go-live and beyond
Map customer workflows directly on the platform and decide what's worth automating, what's worth fixing first, and what's blocked
Improve the underlying processes where it matters — don't automate broken flows, redesign them
Translate business logic into agent behaviour: actions, decision rules, exception paths, fallbacks
Configure and ship agents against real customer systems (ERPs, portals, spreadsheets, email, custom tools)
Write integration code, scripts, and prototypes when the situation calls for it
Debug live agents in production and iterate quickly
Build and own the working relationship with customer stakeholders, from operators to sponsors
Run working sessions, hold your own with technical counterparts, and earn the right to push back
Capture reusable patterns, templates, and runbooks so the next deployment is faster
Send recurring workflow patterns back to Product and Engineering as real signal
What success looks like
Multiple agents in production across clients, with measurable business impact
Customers point to specific KPIs that moved because of your work
Customers treat you as a trusted operator and want you in the room
Process improvements you drove are visible in the customer's day-to-day, not just in the agent
Accounts you own expand because the relationship and the results are both there
Each deployment is faster than the last because you've left behind reusable assets
Experience
5+ years in roles where you've shipped against real customer environments. We're prioritising AI-native candidates: people who have been building, deploying, or operating AI and agentic systems in customer-facing settings, not adjacent to them.
Likely backgrounds: forward-deployed or solutions engineering at an AI-first company · applied AI/ML engineering with direct customer exposure · technical consulting on AI or automation where you owned delivery and the client relationship · operations or product roles where you've built and shipped AI-powered tooling against messy real-world systems.
Retail, e-commerce, or CPG background is a strong plus. Fluency in any operational domain — supply chain, procurement, category management, merchandising, finance ops, supplier management, warehousing — helps you ramp faster. What matters most is that you can pick up a new business quickly, see how to improve it, and build something with AI that actually works.
Skills
Hands-on with modern AI tooling: LLMs, agent frameworks, prompt engineering, evals, MCP, retrieval · strong systems thinking and engineering judgment · process design instinct · comfortable in code-adjacent territory: SQL, Python or JS scripting, APIs, JSON, webhooks · familiarity with ERPs and enterprise stacks is a plus · able to lead a working session, manage a stakeholder, push back on bad scope, and explain trade-offs without hiding behind jargon · fluent English; additional European languages are a plus.
Mindset
Bias to ship. Comfortable with ambiguity, half-built systems, and changing requirements. Low ego, high standards. Customer-obsessed — you build trust by being useful, not by being polished. Commercially aware. Honest about what's working and what isn't.
What we offer
A small, sharp team that values ownership and candour
Real product and culture leverage from day one
Customer-facing impact: your work ships and moves the business
Competitive comp including equity · option to trade cash for equity
How we hire
Online screen
Hiring manager interview (remote or on-site)
Case study and presentation
Founder interview
We're not looking for perfection. We're looking for someone who can walk into a customer's operation, figure out what matters, fix the process, ship the agent, and turn AI into outcomes the business can feel.
Compensation & benefits
Salary: $100k – $200k
Equity details
Type: equity
Details: Option to trade cash for equity
Team
- A small, sharp team that values ownership and candor