Treasure AI
Staff Forward Deployed Engineer — Real-Time Customer Data
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Staff Forward Deployed Engineer — Real-Time Customer Data
Staff Forward Deployed Engineer
(Treasure AI)
About the Role
Treasure AI is the agentic experience platform built to acquire, retain, and grow your most valuable customers. Powered by AI, we combine human creativity with continuous, context-driven action.
Treasure AI is hiring a Staff Forward Deployed Engineer to work with our most strategic global customers—primarily large enterprises in e-commerce and retail. Unlike traditional customer-facing or professional services roles, this position will place you at the nexus of product engineering and customer success, collaborating closely with our customers' engineering and data teams to design, build, and productize real-time data solutions that drive measurable business outcomes.
This role pioneers the technical engagement model for our strategic accounts and sets the benchmark for future Forward Deployed Engineers (FDEs). Your work will define how Treasure AI handles ambiguous system-level challenges, addressing hard problems where business objectives are clear, but the technical execution remains undefined. Expect to explore, define, and build solutions collaboratively with customers and Treasure AI’s real-time platform engineering team.
You will report to the Senior Director of Forward Deployed Engineering and work closely with Real-Time R&D and Platform Engineering.
Responsibilities
Your work will cycle through four core phases—continuously:
1. Explore & Discover
- Partner with the customer to surface the real problem—not just what’s requested—forcing ambiguity to the front.
- Conduct deep technical discovery sessions with the customer’s engineering and data teams to map architecture, constraints, failure modes, and dependencies.
- Identify gaps between stated needs and measurable impact on business outcomes.
- Take the lead in diagnosis, not facilitation—bring informed, insightful perspectives into the room.
2. Define
- Translate vague business objectives into a clear technical problem statement.
- Author technical scoping documents that align stakeholders (customer, Treasure AI R&D, platform engineering) around a shared technical vision.
- Establish measurable success criteria tied directly to business outcomes.
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3. Build
- Design and validate solutions for both sides: the customer and Treasure AI’s product.
- Develop streaming architectures capable of handling real-world complexity (late-arriving events, schema drift, backpressure, partial failures, and sub-second SLAs).
- Make clear, grounded tradeoff decisions and own them fully.
4. Productize
- Derive reusable reference architectures, patterns, and guidelines for broader deployment by the FDE team.
- Objective: Increase—not decrease—maintainability as the product evolves.
A great solution? One that the customer can evolve without increasing burden—no complexity debt allowed.
Job Requirements
| Core Qualifications | Nice-to-Have Pluses |
|---|---|
| 8+ years of software or data engineering experience, including ≥2 years in customer-facing, embedded, or solutions engineering roles. | Experience with real-time personalization, push notification pipelines, or trigger-based marketing (e.g., cart abandonment). |
| Proven hands-on expertise in streaming and event-driven architectures, including Kafka, Spark Streaming, Flink, or Kinesis. | Kotlin/Node.js or Java/Scala development. |
| Advanced fluency in AWS cloud architecture, including scalable data pipelines that integrate Kafka/Flink for streaming, Lambda, Kinesis, etc., handling large-scale event data. | Familiarity with ML model serving in streaming (feature stores, real-time inference). |
| Strong foundation in data engineering fundamentals: pipeline design, SQL, Python, schema modeling, and ensuring data quality. | Prior roles at a data platform, CDP, or martech company. |
| Experience building/integrating with CDP/CDX, marketing automation, or behavioral data platforms. | |
| Greenfield experience: Have successfully led high-risk, undefined technical projects (not book followers). | |
| Bilingual between abstraction and pragmatism: |
- Lead enterprise whiteboard workshops in the morning.
- Be terminal-ready for hands-on coding/debugging by afternoon. | | | Crucial communication: Distill complex architectures into business-aligned narratives for non-technical stakeholders, earning credibility at the executive level. | |
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How You’ll Work
40% customer engagement / 60% engineering (aligned):
- Host regular discovery sessions at the customer’s London office (on-site housing available).
- Collaborate closely with Treasure AI’s real-time platform engineering teams.
- Participate in quarterly leadership meetings, occasionally in European cities.
Key mindset: You’re not a solution-printer, but an agent of “how do we solve this ship-ready problem”. This is a permanent, long-term investment in sustainable gains.
Why This Role
- Real customer adoption, not toy projects.
- Directly impacts Treasure AI’s long-term product vision—you’re building the enterprise real-time experience standard.
- Join a small, highly visible FDE team with deep leadership trust.
- Pioneering realm: RT best practices don’t yet exist; you’ll help craft them.
Physical & Travel Requirements
- Primary: On-site London (committed to UK hybrid policy).
- Travel: ~4 Romania/France/Germany executive flights/year.
Perks & Benefits (UK)
| Culture & Care | Financial Remuneration |
|---|---|
| Competitive salary plus RSU](https://treasurer.ai/what-we-offer/#a-competitive-salary-plus-rsus). | Docfree (medical pathology) + company life insurance (5x annual salary). |
| Salary sacrifice pension plan (7% employer match). | 26 weeks paid leave (including post-partum night nurse). |
| Pre-/post-birth/family-building support via Carrot. | Open-ended, permanent with shared ownership of solutions. |
Treasure AI is committed to creating a diverse, inclusive culture at all levels. We expect perspectives to drive collective creativity, ensuring strong voices are always encouraged and amplified.
Doing more than checking boxes? Be proactive, lead at every level, and influence how great enterprise data experiences are built—today.
Prohibited recruitment (only active contracts accepted; self-submissions decline policified).
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