UMO — a stealth-mode FinTech venture headquartered in Dubai UAE with offices in Lisbon and Kyiv — is building a unified, AI-powered modern money platform spanning fiat, crypto, and investments. They are now seeking an AI Architect and Team Lead to own the core technical design of their AI ecosystem — leading, growing, and mentoring the AI engineering squad, and building production-grade LLM systems, agentic frameworks, retrieval architectures, and intelligence layers that integrate invisibly into real financial workflows. This is a senior role requiring 5+ years of AI engineering experience, genuine team leadership, and deep comfort with regulated, PII-sensitive AI systems. Remote options available for the right candidate.
About UMO — AI-Powered Modern Money Platform
Stage: Stealth-mode FinTech — actively developing MVP and navigating licensing requirements
Mission: Break down traditional barriers to money across access, assets, and experience — for everyone
Team: 100+ people across 20+ nationalities — Dubai HQ, Lisbon and Kyiv offices
Platform: Unified fiat, crypto, and investment platform — AI-native from the ground up
Leadership: True technical and people-leadership autonomy — no micromanagement
The UMO Standard — Benefits & Culture
Leave: 24 days annual leave + dedicated paid sick leave + public holidays
Recharge Week: Two consecutive 4-day work weeks per year after Year 1 — a built-in reset
Setup: Top-of-the-line hardware + home office stipend for wherever you work best
Growth: Dedicated learning budget + accelerated path toward executive-level leadership
Impact: Your architecture shapes the product and company direction — not just executes it
Position Overview
The AI Architect and Team Lead at UMO is a founding technical leadership role at one of the most ambitious AI-native FinTech ventures in the UAE. You will lead the core technical design of UMO’s entire unified intelligence layer — integrating large language models and retrieval systems smoothly with transactional financial infrastructure — while simultaneously leading, mentoring, and growing the AI engineering squad with the expectation that mentorship is a daily practice, not a quarterly event.
This is explicitly a hands-on architecture and leadership role. You will ship code every week. You will own outcomes end to end, including dependencies on other teams. You will act as the “lighthouse” reference point in AI for every other team in the organisation — and you will operate with the kind of genuine technical autonomy that only an AI-native, trust-driven culture can actually provide. If intelligence that feels invisible, compliant, and deeply integrated into financial workflows is what you want to build, UMO has designed this role for you.
Why This Role Matters: Most FinTech platforms add AI as a layer on top of existing systems — a feature, not a foundation. UMO is different: the AI is the platform, designed from day one to make the experience of money feel genuinely intelligent, adaptive, and human. As the AI Architect, you are not retrofitting intelligence into a legacy system. You are designing the intelligence layer that will define how a new generation of financial platform serves a business owner, a freelancer, an artist — anyone. That is a product design challenge, an engineering challenge, and a responsibility that very few roles in global FinTech currently offer.
What You’ll Own — Key Responsibilities
AI Squad Leadership & Mentorship
- Lead, grow, and mentor a high-performing AI engineering squad — running regular code reviews, sharing architectural context across the team, and making mentorship an expected and visible daily practice rather than an occasional management activity
- Own outcomes end to end as Team Lead — including dependencies on other teams — with success defined by features that are live in production, not tasks that are merely closed in a sprint board
- Act as the technical “lighthouse” — the reference point and authority in AI architecture for every other engineering team across UMO’s multidisciplinary organisation — providing guidance, design reviews, and cross-team alignment on AI system decisions
- Stay hands-on every week — shipping code regularly as a practising engineer-leader, maintaining the technical depth and production awareness that genuine architectural leadership in an AI-native FinTech startup requires
Core AI Architecture & Intelligence Layer Design
- Design and build the fundamental technical blueprints for UMO’s unified intelligence layer — integrating large language models and retrieval systems smoothly and securely with the transactional financial infrastructure that underlies the platform
- Lead the development of deterministic-agentic bridges — designing the architectural patterns that allow complex autonomous AI tasks to operate within predictable, secure, and regulatory-compliant financial boundaries where the consequences of unpredictable behaviour are real and significant
- Take full responsibility for bringing machine learning models from research prototypes into stable, highly performant production systems — owning the full journey from experimentation through to production monitoring and continuous improvement
- Collaborate closely with backend and data engineers to take agentic workflows from prototype to reliable, monitored production systems — applying practical experience across retrieval, memory, and orchestration layers to ensure production outcomes, not just impressive demos
Agentic Systems, Retrieval & Evaluation
- Design and implement production-grade agentic AI workflows — including multi-agent orchestration, tool use, memory management, and reliable execution patterns for complex financial automation use cases within UMO’s regulated FinTech environment
- Build retrieval architectures and semantic search systems that support UMO’s intelligence layer — applying practical RAG (Retrieval-Augmented Generation) design across financial document retrieval, user context management, and knowledge base integration
- Develop meaningful AI evaluation and measurement systems — covering quality, cost, and latency in production — so that every AI capability deployed can be quantifiably measured, understood, and improved over time rather than simply shipped and hoped for
About You — Requirements
Engineering Leadership & Technical Depth
- 5+ years as a senior engineer with real team leadership experience — as a Tech Lead, Team Lead, or equivalent — combined with a deep architectural background in production-grade machine learning and AI systems; adjacent leadership is fine but the leadership itself must be genuine and demonstrable
- Proven experience taking agentic systems into production — not just designing or prototyping them, but shipping live multi-step automated workflows that real users depend on, with monitoring, incident handling, and continuous improvement in place
- Strong Python engineering skills alongside asynchronous execution models — combined with the engineering rigour to produce clean, testable, maintainable code in a regulated environment where correctness and auditability matter as much as performance
- Active use of AI coding tools (Cursor, Claude Code, GitHub Copilot, or similar) as a core part of your daily engineering workflow — expected practice at UMO, and especially important for the person architecting the company’s AI systems
AI Technical Skills
- Deep comfort with modern LLM tooling and orchestration frameworks — including practical production experience with LLM inference, prompt engineering at scale, context management, and the reliability patterns needed to make LLM-powered systems behave predictably in financial applications
- Practical experience with semantic search and retrieval architectures — including vector-based retrieval, hybrid search, re-ranking, and the retrieval augmentation patterns that support accurate, context-aware AI responses in production systems
- Experience handling PII and sensitive data with LLMs in regulated environments — understanding the data minimisation, access control, logging, and audit requirements that apply when AI systems process financial and personal information
- Comfort designing and shipping AI systems within strict security, compliance, and audit boundaries — this is the must-have; fintech or crypto domain-specific experience is helpful but not required
Bonus Points (Nice to Have)
- Startup exposure — experience keeping technical designs flexible and adaptive as product targets evolve rapidly in an early-stage environment where priorities shift and architecture decisions have long leverage
- Fintech or crypto literacy — previous experience building software inside regulated financial or web3 spaces; nice to have, not required — UMO explicitly acknowledges the AI talent pool with fintech experience is small
- Proven track record of shipping live, multi-agent automated workflows to production at a scale that demonstrates genuine agentic deployment maturity beyond prototype or POC environments
Why This AI Architect Role at UMO FinTech Is Exceptional in 2026
Most AI engineering roles in 2026 involve integrating AI into existing systems that were never designed with intelligence in mind. UMO is building the opposite — a money platform where AI is the architecture, not an add-on, and where the intelligence layer is designed from day one to make financial experience feel genuinely adaptive, personal, and human for everyone who uses it. That is a genuinely different engineering challenge — and it demands a genuinely different kind of AI Architect.
For a senior engineer with the LLM depth, agentic production experience, regulated-environment comfort, and team leadership credibility this role requires, UMO offers the rarest combination available in the global AI talent market: full architectural ownership of an AI-native platform, a world-class benefits package, remote flexibility, genuine executive career trajectory, and the mission-level significance of building the AI layer that could change how hundreds of thousands of people experience money. If you are ready to build something that matters from the ground up, UMO is where you do it.
Who Should Apply?
- Senior AI Engineers with Team Leadership Experience: With 5+ years of production AI/ML system ownership and genuine Tech Lead or Team Lead credentials — ready to own both the architecture and the people side of a high-performing AI squad in an AI-native FinTech
- Production LLM and Agentic Systems Engineers: Who have shipped live agentic workflows, multi-agent orchestration, or LLM-powered production systems — not just prototyped them — with monitoring, reliability, and continuous improvement already in place
- AI Architects from Regulated Environments: With demonstrated experience designing AI systems that handle PII and sensitive data within security, compliance, and audit boundaries — comfortable with the guardrails that regulated financial services require without being constrained by them
- Startup-Minded Senior Engineers: Who have kept AI architecture flexible and adaptive as product priorities evolved rapidly in early-stage environments — able to design for the current MVP and the eventual scaled platform simultaneously
- Dubai-Based or Remote AI Leaders: Seeking a full-time founding AI architecture role with genuine ownership, a learning budget, 24 days leave, hardware setup, executive-level career trajectory, and the rare opportunity to design an AI-native money platform from first principles at a stealth UAE FinTech
