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As our AI Product Manager, you’ll be defining and delivering the next generation of AI-powered products at Sokin, leveraging agentic AI, large language models, and intelligent automation to fundamentally transform how businesses move, manage, and optimise money across borders. You’ll design and ship products that bring autonomous AI agents into the heart of the product: payments, treasury, and company operations. This means building intelligent workflows that can independently handle tasks and deliver value. You’ll create seamless experiences where clients benefit from AI-driven efficiency without needing to understand the underlying complexity. You’ll also be responsible for communicating the customer value of agentic AI to internal stakeholders and clients — articulating where autonomous agents offer genuine advantages over legacy systems, when AI-driven orchestration can reduce cost and settlement time, and how intelligent automation can unlock new business models. This includes monitoring the rapidly evolving AI ecosystem, evaluating new models, protocols, and infrastructure (such as MCP and A2A), and making informed decisions about what to build on. Success means delivering products that offer innovative value for our customers — while maintaining the security, transparency, and compliance that enterprise clients demand.
Job Responsibility:
Define and communicate the AI product roadmap aligned to the company’s vision across payments, treasury, compliance automation, and agentic commerce
Identify and prioritise high-impact use cases for agentic AI across Sokin’s product suite, from autonomous reconciliation and intelligent payment routing to AI-driven KYC/AML workflows
Work directly with a cross-functional team of AI/ML engineers, data scientists, and platform engineers to deliver value iteratively and often
Conduct market research and competitive analysis to stay ahead of trends in LLMs, AI agents, agentic payments, and fintech automation
Spend time with customers and internal stakeholders to discover new AI product opportunities, identify improvements, and validate solutions
Collaborate with engineering, design, compliance, marketing, and sales teams to assess the value, feasibility, viability, and safety of AI-powered solutions
Define product requirements for AI systems, including model selection criteria, evaluation frameworks (evals), guardrails, latency targets, and human-in-the-loop checkpoints
Own the responsible AI framework for your products, ensuring fairness, explainability, auditability, and compliance with the EU AI Act and relevant financial regulations
Work closely with product marketing and sales to articulate the value of AI features and launch new products to clients
Monitor AI product performance using both traditional product metrics and AI-specific evaluations (accuracy, hallucination rates, agent task completion, cost-per-inference) to drive continuous improvement
Act as the primary point of contact for all AI product-related inquiries across the business
Requirements:
Fintech & Payments Expertise: Experience building products in fintech space — specifically in payments, treasury, FX, or financial infrastructure
Strong understanding of traditional payment rails and protocols (SEPA, Faster Payments, ACH, SWIFT) and how they intersect with emerging technologies like stablecoins and blockchain-based settlement
Understanding of how card acquiring works, the key players in the payment processing chain, and the mechanics of cross-border money movement
Understanding of how stablecoins work across different setups and blockchains
Comfort working with compliance, risk, and legal stakeholders, and understand the regulatory landscape for financial services, including PCI-DSS, PSD2/PSD3, GDPR, and SOC 2
Agentic AI & Technical Depth: Hands-on experience with the latest LLMs and AI models (from Anthropic, OpenAI, Google, and open-source providers), with a deep understanding of their capabilities, limitations, and cost/performance trade-offs
Understanding of the architecture and design patterns behind agentic AI systems — multi-agent orchestration, tool use and function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows
Familiarity with emerging agent interoperability standards such as the Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocol, and understand their implications for building composable, production-grade AI products
Ability to design and evaluate AI systems using modern evaluation frameworks (evals, benchmarks, red-teaming) and understand the difference between measuring traditional software and probabilistic AI outputs
Experience with or strong understanding of prompt engineering, fine-tuning strategies, and the trade-offs between different AI deployment approaches (API-based, self-hosted, edge)
Understanding of the regulatory and ethical considerations unique to AI in financial services, including the EU AI Act’s risk classification, explainability requirements, and the implications of autonomous AI decision-making in payments
Strong understanding of SDLC and internal processes of the company
Product & Leadership Skills: Driven to make a difference and want to fully own your AI product roadmap from vision to delivery
Someone who enjoys getting into the technical details — can read an architecture diagram, understand a data pipeline, and debate model selection trade-offs with engineers
Hands-on experience with AI prototyping and automation, including building proof-of-concept agents, working with no-code/low-code AI tools, or scripting with Python
Enjoy working in cross-functional teams alongside engineers, data scientists, designers, and other functions to deliver value to users, and have familiarity with the technical side of the development process
Good understanding of technical concepts and can work closely with ML engineers to find the best solution to a problem — balancing accuracy, latency, cost, and safety
Love solving problems in innovative and creative ways, and are energised by the pace of change in the AI landscape
Right to work in the jurisdiction that they are looking to work in
Nice to have:
Experience building or managing AI products in a regulated industry (fintech, healthtech, insurtech)
Experience in launching agentic automations inside the company
Experience with AI agent frameworks (e.g., LangChain, CrewAI, AutoGen) or building MCP-based integrations
Understanding of MLOps practices, model monitoring, and AI observability tooling
Prior experience in a startup or scale-up environment with a bias toward shipping and iterating quickly