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описание
Capital.com is a financial services company developing digital asset trading products and related internal systems. The company uses AI-driven initiatives, financial integrations, and automation to support operational workflows.
задачи
Develop and maintain internal services, tools, APIs, automation scripts, and AI-enabled workflows;
Design and implement AI agents, multi-step agent flows, and automation pipelines for internal business processes;
Build integrations with internal and third-party systems, including financial platforms, payment providers, reporting tools, Jira, Confluence, Okta, Slack, AWS, and other enterprise systems;
Develop AI-powered features for intelligent data processing, document analysis, classification, anomaly detection, workflow automation, and decision support;
Integrate LLMs and AI services into internal applications using APIs, orchestration frameworks, vector databases, and retrieval-augmented generation;
Create and maintain automation flows connecting AI agents, APIs, databases, notifications, approval workflows, and local and remote MCP servers;
Investigate, troubleshoot, and resolve issues related to financial integrations, API failures, data inconsistencies, and automation errors;
Write clean, efficient, secure, and well-documented code following software engineering best practices;
Implement CI/CD pipelines and automated testing frameworks;
Optimize system performance, reliability, observability, and security;
Contribute to architectural decisions, participate in code reviews, and support engineering standards;
Identify opportunities to improve manual processes through automation, AI, and better system integrations.
требования
3–5+ Years of professional experience as a Python Developer or AI Engineer;
Strong proficiency in Python 3.x, including asynchronous programming and REST API development;
Experience with FastAPI, FastMCP, Flask, or Django;
Practical experience building or integrating AI-powered solutions in production or near-production environments;
Experience with LLM APIs and AI platforms such as OpenAI, Anthropic, AWS Bedrock, or Google Vertex AI;
Experience designing AI agent workflows, tool-calling flows, prompt-driven automation, or multi-step AI orchestration;
Understanding of prompt design, retrieval-augmented generation, embeddings, vector databases, structured outputs, evaluation, and guardrails;
Ability to integrate AI capabilities into existing services, internal tools, and automation workflows;
Strong experience with API integrations, authentication, OAuth2, webhooks, error handling, retries, rate limits, and secure data exchange;
Solid understanding of SQL and relational databases such as PostgreSQL or MySQL;
Experience troubleshooting API integrations, data synchronization issues, automation failures, and production defects;
Basic proficiency in HTML, CSS, and JavaScript for lightweight frontend interfaces or internal admin dashboards;
Experience with Docker and Kubernetes;
Familiarity with GitLab CI/CD or similar CI/CD pipelines;
Experience with financial data processing, reconciliation, reporting automation, or transaction monitoring;
Understanding of risk, compliance, and operational controls in financial environments;
Understanding of secure coding practices, secrets management, access control, and secure data handling;
Strong analytical, debugging, and problem-solving skills;
Excellent communication skills and ability to work with technical and non-technical stakeholders;
Nice to have: AWS services, Kubernetes deployments and management, enterprise tool integrations such as Jira API, Okta API, and Slack API, infrastructure as code, DevOps practices, ELK, Prometheus, Grafana, secure coding and compliance in fintech or regulated environments, math and algorithms behind AI.
условия
Competitive salary;
Annual performance bonus;
Annual leave;
Employee referral program;
Medical insurance and pension benefits;
Location-specific benefits and perks;
30 Extra days to work remotely from anywhere in the world, with some restrictions;
Two additional paid volunteer days per year;
The hiring process may use AI tools for reviewing applications, analyzing resumes, or assessing responses; final hiring decisions are made by humans.
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