AI Engineer
Sokin
AI Engineer
As an AI Engineer, you will be at the forefront of designing, building, and deploying intelligent systems that transform how Sokin delivers global payment services. You will architect end-to-end agentic workflows, leverage large language models for automation across the software development lifecycle, and apply AI to solve complex challenges in cross-border payments, compliance, and treasury operations.
This role sits within the AI team and requires deep hands-on experience with agentic code generation tools such as Claude Code, advanced context management techniques including RAG and prompt orchestration, and a strong understanding of fintech domain requirements. You will work across the full stack, collaborating closely with engineering, product, and compliance teams to ship AI-powered capabilities that are production-grade, secure, and compliant.
About Us
Sokin is a next-generation B2B financial services provider, enabling businesses to make and receive global payments with greater speed, lower cost, and total transparency.
Our mission is simple: we’re simplifying global business - so businesses thrive wherever they choose to grow. We deliver services across:
• Global payments and receivables
• Foreign Exchange (FX)
• Treasury management
• Finance reconciliations
We are rapidly expanding, with established presence in EMEA, APAC, and North America, backed by a strong global infrastructure and industry-leading partners, we are redefining how businesses move money worldwide.
Our clients span industries from sports and entertainment to logistics and travel, and our community is growing rapidly. As we continue to expand, we’re building a team of exceptional people who share our ambition to transform the future of global payments.
Key Responsibilities
Agentic AI Development: Design, build, and maintain end-to-end agentic workflows and AI-powered automation systems using tools such as Claude Code, LangChain, CrewAI, or equivalent frameworks. Develop planning agents, orchestration layers, plugins, and skill-based architectures that reliably solve complex, multi-step tasks.
Agentic Code Generation: Lead the adoption and optimisation of agentic code generation across the engineering organisation. Build and refine AI-assisted development pipelines that accelerate feature delivery, enforce code quality standards, and integrate seamlessly into CI/CD workflows.
Context Management and RAG: Architect and implement Retrieval-Augmented Generation (RAG) pipelines and advanced context management strategies to ensure AI agents operate effectively within large codebases, documentation, and domain-specific knowledge bases. Evaluate and implement frameworks for context window optimisation, memory management, and knowledge retrieval.
Full SDLC AI Integration: Embed AI capabilities across the entire software development lifecycle, from requirements analysis and design through to code generation, testing, code review, deployment, and monitoring. Drive adoption of AI-assisted tooling for documentation, test generation, and incident triage.
Fintech Domain Application: Apply AI to core fintech features driving new value creation for customers and optimizations. Ensure all AI systems meet the security and compliance requirements of a regulated financial services environment.
Production AI Systems: Own the deployment, monitoring, and continuous improvement of AI systems in production. Implement observability, guardrails, evaluation frameworks, and feedback loops to ensure reliability, safety, and measurable business impact.
Cross-Functional Collaboration: Work closely with product managers, engineers, compliance, and operations teams to identify high-impact AI opportunities, define requirements, and deliver solutions that align with business objectives and regulatory standards.
Knowledge Sharing and Mentorship: Establish best practices for AI engineering within the team. Mentor engineers on effective use of agentic tools and AI-assisted workflows, and contribute to internal documentation and training.
Education
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field (or equivalent professional experience).
Experience
3+ years of professional/or non-commercial but provable experience in AI/ML engineering, with at least 1 year focused on agentic AI systems or LLM-based application development.
Demonstrable experience with end-to-end agentic code generation using Claude Code, Cursor, GitHub Copilot Workspace, or equivalent tools. You must be able to showcase your work: agentic flows, planning agents, multi-step automation, and production deployments.
Proven track record of building and deploying RAG pipelines, context management solutions, and knowledge retrieval systems at scale. If no commercial experience, proven working showcases.
Hands-on experience across the full software development lifecycle (SDLC), including deployment and maintenance with AI-assisted tooling, including agentic automations for code generation, testing, review, and deployment.
Experience working in fintech, payments, crypto or a regulated financial services environment is strongly preferred.
Experience designing and implementing plugin or skill-based architectures for AI agents.
Technical Skills
Expert proficiency in Python, Node.js; additional experience with Rust, Go is a strong plus.
Deep working knowledge of LLM APIs and frameworks: Anthropic Claude API, OpenAI API, LangChain, LlamaIndex, CrewAI, AutoGen, or equivalent.
Hands-on experience with agentic frameworks and orchestration patterns: tool use, function calling, multi-agent coordination, chain-of-thought planning, and self-reflection loops.
Strong experience with RAG architectures, vector databases (e.g., Pinecone, Weaviate, pgvector, ChromaDB), embedding models, and retrieval strategies.
Proficiency with cloud platforms (AWS and/or GCP), containerisation (Docker, Kubernetes), and CI/CD pipelines (GitHub Actions).
Experience with prompt engineering, evaluation frameworks (e.g., RAGAS, DeepEval), and AI safety/guardrail implementation.
Familiarity with payments infrastructure, messaging standards (ISO 20022, SWIFT), and fintech APIs.
Understanding of compliance-relevant AI considerations: data privacy (GDPR), auditability, explainability, and PCI-DSS requirements for AI systems handling financial data.
We appreciate you may not tick all the boxes! Essentially, we are looking for motivated and driven candidates that can demonstrate their interest and if you have integrated AI into a product we want to hear from you!
Portfolio and Demonstration
For candidates without commercial experience are expected to demonstrate their expertise through:
A portfolio or examples of agentic AI systems you have built, including architecture diagrams, workflow descriptions, and outcomes.
Live demonstration or recorded walkthrough of agentic code generation workflows, showcasing planning, execution, and iteration loops.
Examples of RAG implementations, context management approaches, or plugin/skill architectures you have designed and deployed.
Evidence of AI integration across the SDLC, including metrics on productivity improvement, code quality, or deployment velocity.
Please note, candidates will need to have the right to work in the jurisdiction that they are looking to work in.
Sokin is an equal opportunities employer and committed to maintaining an inclusive work environment. As a growing global startup with bases across multiple countries, we were established on and continue to promote an agile, flexible working culture. Please reach out to discuss any accommodations you may require during the recruitment process.