Staff Forward Deployed Engineer — Real-Time Customer Data

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: Treasure AI is hiring a Staff Forward Deployed Engineer dedicated to some of our most strategic global customers — think large enterprises in the e-commerce and retail space. This is not a typical customer-facing or professional services role. You will be embedded at the intersection of product engineering and customer success, working directly alongside the customer’s engineering and data teams to design, build, and productize real-time data solutions that drive measurable business outcomes. The goal is for you to define the technical engagement model for our strategic accounts, and set the standards and patterns our other FDEs will adopt. This role exists because the problems we’re solving here are genuinely hard: business objectives are clear, but the system-level “how” is not. You will explore, define, and build those answers — together with the customer and together with Treasure AI’s real-time platform engineering team. In this role you will identify and frame new problem domains for the FDE team to pursue (you don’t just get assigned hard problems, you find them). You will report to the Senior Director of Forward Deployed Engineering and collaborate closely with our Real-Time R&D and Platform Engineering teams.

Responsibilities: Our customers operate at a global scale and need to act on customer behaviour in real time — think cart abandonment personalisation, push notification triggers, and dynamic offer delivery within seconds of a web or app event. In this role you will define and execute how to close the gap between raw behavioural data and a personalised customer experience. Your work will cycle through four phases — continuously:

• Explore & Discover – Work with the customer to surface and frame the real problem, not just the stated requirement. Proactively find and articulate issues the customer has not yet thought of. Run deep technical discovery sessions with the customer’s engineering and data teams to understand current architecture, constraints, and failure modes. Identify gaps between what the customer believes they need and what will actually move the needle on business outcomes. Map dependencies across systems before a line of design work begins. Bring a point of view into the room: you’re not facilitating, you’re diagnosing.
• Define – Translate ambiguous business objectives into a clear system-level problem statement. You own the translation layer between business intent and technical architecture. Author technical scoping documents that align customer stakeholders, Treasure AI R&D, and platform engineering around a shared understanding of the problem. Define success criteria that are measurable and tied to business outcomes.
• Build – Design and validate solutions on both the customer side and the Treasure AI product side. Design streaming architectures that handle real-world complexity: late-arriving events, schema drift, backpressure, partial failures, and sub-second SLA requirements. Drive technical decisions with clear rationale; when tradeoffs exist, you name them explicitly and own the call.
• Productize – Where solutions are generalisable, drive them into capabilities other customers can use. Distill what you’ve built into reusable reference architectures, implementation guides, and decision frameworks for the broader FDE team. A great solution in this role means: quality is maintained after you move on, and it gets easier to maintain as the product evolves — not harder.

Job Requirements:

• 8+ years of software or data engineering experience, with at least 2 years in a customer-facing, embedded, or solutions engineering capacity.
• Strong hands-on experience with streaming and event-driven architectures — Kafka, Flink, Kinesis, Spark Streaming, or equivalent (DynamoDB and MemoryDB/Redis).
• AWS Cloud Fluency - understand how to design scalable end-to-end architectures and pipelines on large volumes of data (think Kafka/Flink for streaming + AWS Lambda + Kinesis).
• Solid data engineering fundamentals: pipeline design, SQL, Python, schema modelling, data quality.
• Experience building or integrating with CDP, marketing automation, or behavioural data-management platforms.
• Proven ability to go from ambiguous problem to working system — you’ve done greenfield technical work where no playbook existed.
• Capable of operating at both the whiteboard and the terminal; you can lead a technical workshop with a customer’s engineering team in the morning and be deep in code in the afternoon.
• Strong written and verbal communication — you can make a complex architecture legible to a non-technical stakeholder and earn trust at the top most levels of an organisation.

Strong Plus:

• Experience with real-time personalisation, push notification pipelines, or cart-abandonment / trigger-based marketing systems.
• Kotlin and Node/Javascript or Java/Scala.
• Familiarity with ML model serving in streaming contexts (feature stores, real-time inference).
• Prior work at a data platform, CDP, or martech company.

How You’ll Work: This is a 40% customer engagement / 60% engineering role. Concretely, that means:

• Regular working sessions and workshops with the customer’s engineering and data teams at their London office.
• Collaborative design and build work with Treasure AI’s real-time platform engineering team.
• Quarterly leadership meetings, occasionally in continental Europe.
• You are not an order-taker — you have genuine influence over what gets built and how.
• This role is permanent and open-ended. You are not parachuting in for a fixed engagement. You are building something durable.

Why This Role: You will work on a real hard problem with a real large customer — not a demo environment. Your work has a direct line to product evolution at Treasure AI; you are building the playbook for real-time customer data at enterprise scale. You will be part of a small, senior FDE team where your work is visible to leadership. The problems here are genuinely new — RT best practices don’t fully exist yet, and you’ll help write them.

Physical Requirements: Working out of the London, UK office according to our “Global Hybrid Working Policy.”

Travel Requirements: Occasional travel within Europe for quarterly executive meetings (~4x/year).

Perks and Benefits (UK): Competitive compensation packages, Salary Sacrifice pension plan with 7% employer match, Supplemental medical and dental cover offered & 5X annual salary for life cover provided, Restricted Stock Units (RSU), Up to 26 weeks paid parental leave including a post-partum night nurse, Comprehensive support and access to care for everyone, everywhere through Carrot – our global reproductive health and family-building benefit.

Our Dedication to You: We value and promote diversity, equity, inclusion, and belonging in all aspects of our business and at all levels. Success comes from acknowledging, welcoming, and incorporating diverse perspectives. Diverse representation alone is not the desired outcome. We also strive to create an inclusive culture that encourages growth, ownership of your role, and achieving innovation in new and unique ways. Your voice will be heard, and we will help amplify it.

Agencies and Recruiters: We cannot consider your candidate(s) without a contract in place. Any resumes received without having an active agreement will be considered gratis referrals to us. Thank you for your understanding and cooperation!

This description captures the core of the role today. As we adopt AI and new ways of working, responsibilities may evolve, and we encourage team members to take initiative, lean into change, and help expand the impact of their role beyond what’s listed here.