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AI Engineer · Belgrade

Job in London, Greater London, W1B, England, UK
Listing for: Sokin Global Currency Account
Full Time position
Listed on 2026-06-08
Job specializations:
  • Software Development
    AI Engineer, Software Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI Engineer · Belgrade  ·

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.

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, Lang Chain, 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, Git Hub Copilot Workspace, or equivalent tools. You must be able to showcase your work: agentic flows, planning agents, multi‑step…
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