use advanced AI to enable scalable efficiency for financial services companies, combining world-leading Natural Language Processing (NLP) and Large Language Model (LLM) expertise with deep financial services domain experience to drive enterprise-wide productivity. We're using the latest in AI to automate and innovate, empowering financial service businesses to achieve exceptional productivity and compliance outcomes. Role Overview … financial services or adjacent sectors. You likely come from a Big 4 consultancy, technology advisory practice or a similarly demanding environment. From this background you bring: Rigorous client-facing experience: doing discovery, scoping, workshops, POCs, RFPs, not just writing proposals, but engaging deeply with clients at multiple levels (operations, risk, compliance, executives). Structured, analytical problem solving: you break … s AI/LLMs meet their needs; help them navigate trade-offs (accuracy, risk, explainability, privacy). Provide feedback to Product and Engineering on feature requests, prioritisation, bug-fixes, userexperience, based on what you see in the field. Help define best practices, patterns, reusable assets (e.g. architecture templates, demo scripts, integrations) to speed up future engagements. Mentor More ❯
closely with a small, smart team Solving real customer problems — not just ticking off Jira tickets Contributing to a high-trust, low-process engineering culture Main Skills Needed: Commercial experience across frontend, backend, and infrastructure Confident with TDD and continuous delivery practices Comfortable with pairing, refactoring, and designing for simplicity Proactive mindset — you own problems and get things done … early-stage or scale-up environments What's in It for You: True flexibility: remote-first, low meeting load, high autonomy Clear impact: your code shapes the product and userexperience Culture that backs its values — real testing, real ownership Early-stage traction with scale-up potential A genuinely collaborative, high-performing team Let's skip the hard More ❯
group of backend and data engineers. Conduct code reviews, establish engineering best practices, and foster a culture of technical rigor. Collaborate Across the Product Lifecycle: Work closely with Product, UX, DevSecOps, and Frontend teams to deliver features that are reliable, developer-friendly, and intuitive. Who We're Looking For Backend Engineering Expertise: 5+ years designing and building backend SaaS applications … ideally with Python and Go experience with quality-centric approach. Product & Platform Mindset: You've owned backend product roadmaps and can translate user needs into scalable technical solutions. Cloud-Native Proficiency: Experience building distributed backend services on AWS or similar (Lambda, ECS, DynamoDB/Postgres, API Gateway, queues, event systems). Team Leadership: Previous experience leading … backend or cross-functional engineering teams coaching, growing engineers, setting standards. Distributed Data Systems Knowledge: Experience with Postgres, ClickHouse, Kafka, Redis, or similar high-throughput storage and messaging technologies. System Design Strength: Comfortable with designing modular API boundaries, microservices, workflow orchestration, and secure multi-tenant SaaS systems. DevSecOps Knowledge: Experience with DevSecOps workflows, IaC (Terraform/CDK/ More ❯
