About this role

Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future.

Senior Full-Stack Engineer — Flow (AI Agent Platform) Location: London Victoria Office Work Pattern: Hybrid (4 days office, 1 day remote) Team: Flow (Core AI Infrastructure) About the Role Flow is our internal AI agent platform. This isn't a basic chatbot bolted onto a help center; it is core agentic infrastructure that reaches across our data warehouse, services, and central systems to execute complex work on behalf of the business.

Flow powers both internal and client-facing workflows, delivering true automation and replacing traditional ticketing queues with instant, intelligent actions. We are looking for a Senior Full-Stack Engineer to help us transition Flow from a fast-moving internal product to durable, productionized platform infrastructure. You will own complex features end-to-end—including agent workflows, reasoning UIs, and cross-system integrations—while raising the engineering bar and shaping the technical direction of a small, autonomous team.

This role sits at the intersection of agentic AI and live operational workflows within a regulated fintech environment. The surface area is the entire company, and your impact will be visible within weeks. What You'll Do Build Action-Oriented Agent Workflows: Design multi-step orchestration, tool use, and retrieval grounded in our data stores using the Strands Agents SDK. Architect End-to-End Features: Own development across a React/TypeScript frontend and Python/FastAPI backend, balancing rapid iteration with platform maintainability.

Own the Reasoning Layer: Extend our Chain-of-Thought UI to ensure explainability. In a regulated environment, showing why an agent made a decision is a core feature, not a nicety. Make Agents Measurably Reliable: Build and extend our evaluation harness ( Ragas ) and observability platform ( Langfuse , with session continuity) so we ship changes based on evidence, not vibes. Define Evaluation Strategies: Build custom evaluators, datasets, benchmarks, and automated regression suites to catch quality regressions before they hit production.

Integrate Systems & Clouds: Connect internal APIs, data warehouses, email, and cross-cloud GCP/AWS services with robust error handling and distributed tracing. Industrialize Prototypes: Drive the discover → industrialize → productionize lifecycle, turning promising AI prototypes into hardened, daily-deployed services on CD pipelines. Mentor & Lead: Uplift mid-level engineers through code reviews, pair programming, and establishing scalable engineering patterns.

Collaborate Cross-Functionally: Partner with Product, Ops, Trading, and Treasury to identify high-value workflows worth automating (and ruthlessly deprioritize the ones that aren't). The Tech Stack Frontend React, TypeScript Micro-frontend architecture Chain-of-Thought / Agent-reasoning UI Vite, Vitest Backend & AI Python, FastAPI Strands Agents SDK (Agent Orchestration) AWS Bedrock RAG / Advanced Retrieval Ragas (Evaluation), Langfuse (LLM Observability) Infrastructure AWS (ECS Fargate, Lambda, API Gateway, S3) with cross-cloud GCP integration Terraform, GitHub Actions Docker Event-driven integration patterns What We're Looking For Must-Haves 5+ years of professional software engineering experience.

Strong Python Backend Expertise: Deep experience with FastAPI (or Django/Flask), asynchronous programming, clean architecture, and writing production-grade code. Strong React & TypeScript Skills: Ability to architect non-trivial frontends with sound state management, performance optimization, and comprehensive testing. System Design Judgment: A proven track record of designing scalable, maintainable systems and clearly articulating architectural trade-offs.

API & Integration Skills: Proficiency with REST, streaming ( SSE/WebSockets ), and the real-world complexities of stitching together messy upstream systems. Data Proficiency: Strong SQL/NoSQL skills, query optimization, and data modeling. Testing & Ownership Mindset: You treat testing as a core part of the development lifecycle and proactively drive features from ambiguous ideas to production. Excellent Communication: Ability to explain technical decisions to both engineers and non-technical stakeholders, alongside a passion for writing useful documentation.

Nice-to-Haves Agentic AI Experience: Hands-on experience with agent orchestration (Strands, LangGraph, AutoGen, or similar), RAG, tool use, and context engineering. Production LLM Systems: Familiarity with LLM observability (Langfuse), evaluation (Ragas), token/cost management, and reliability patterns. AWS Depth: Experience with Lambda, ECS, Bedrock, or equivalent cloud services (cross-cloud exposure is a major plus).

Event-Driven Architectures: Experience with event streaming and message brokers. Regulated Environments: Experience working within fintech, compliance, or similar sectors with strict data-residency and auditability constraints. Micro-frontends & IaC: Experience with micro-frontend architect

Source listing: greenhouse_ebury