Senior Forward Deployed Engineer
Listed on 2026-10-05
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Treasure AI:
Treasure AI is the agentic experience platform built to acquire, retain, and grow your most valuable customers. Powered by AI, Treasure AI is shaped by human creativity and always-on through continuous, context-driven action.
Furthermore, Treasure AI employees are enthusiastic, data-driven, and customer-obsessed. We are a team of drivers-self-starters who take initiative, anticipate needs, and proactively jump in to solve problems. Our actions reflect our values of honesty, reliability, openness, and humility.
Your Role:The most interesting AI problems are not in a lab. They are inside real companies, sitting on real customer data, attached to real revenue. That is where we work.
Treasure AI is hiring a Senior Forward Deployed Engineer to design and ship GenAI and customer-data systems with our customers - then turn what we learn into new product features or product improvements. You will sit with customers’ technical teams, go from ambiguous business problems to working systems, and feed the hard parts back into the Treasure AI R&D team.
This is not a consulting or professional services role. You are an engineer who engages with customers, innovates and deploys with them.
The job’s core principles are built around the loop below:
Delta- solve the customer's problem.
Work with their engineers and data teams. Understand what actually matters. Design and build the system. Leave something they can run without you.
Echo- redefine the problem for the product.
Customer A needs X is not the end of the thought. The job is this class of customers needs Y. Write the proposal. Open the PR. Co-design with Engineering.
Product- make Delta easier the next time.
What you learn in the field shapes what we build. A better product makes the next engagement sharper. You are accountable for closing that loop, not just one side of it.
Responsibilities:- Run discovery that finds the real problem, not just the stated one
- Be the go-to expert to recommend the best solution for high-priority use cases, even if the solution does not always fully exist OTB and requires custom changes to product
- Turn messy customer data and unclear objectives into a scoped, measurable system
- Build production GenAI, ML, and customer-data solutions - pipelines, models, agents, activations - in code, not slides
- Leave work that stays correct after you move on, and gets easier as the product evolves
- Abstract one-off work into reusable patterns, code templates, reference implementations, and product proposals
- 5-7+ years in software or data engineering, including time in a customer-facing, embedded, or solutions role
- Strong fundamentals:
Python, SQL, pipelines, data modeling, production judgment or Java script, Nodejs, Typescript - Hands-on with data platforms, ML/AI systems, or customer-data / CDP / martech - or the ability to get there fast
- A track record of going from ambiguous problem to working system
- Clear writing and clear thinking. You can explain a hard system to a business stakeholder and defend a technical call with evidence
- Comfort operating inside a customer's organization without formal authority
- Bonus: applied GenAI or ML in production (agents, scoring, recommendations, classification); prior work at a data platform or applied-AI company; you've turned field work into a library, a template, or a product change.
Roughly 60% with customers, 40% building products. You will own your engagements, and work alongside Staff and Principal FDEs on the hardest ones.
Why this:You will work on live problems at the intersection of GenAI, ML and customer data - the kind that change how a business talks to its customers, not a demo that dies in a slide deck. The bar is high, the team is collaborative and…
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