{"id":2699558,"url":"https://alion.io/job/capital-com-platform-architect","title":"Platform Architect","company":{"id":949,"name":"Capital.com","domain":"capital.com","url":"https://alion.io/company/capital","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":82,"open_postings":13,"ghost_share":0,"stale_share":0.692,"repost_share":0.077,"time_to_fill_p50_days":55,"computed_at":"2026-10-16T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland","Limassol, Cyprus","Sofia, Bulgaria"],"countries":["PL","CY","BG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":63000,"max_usd":114000,"period":"year","method":"role_seniority_country_cell","sample_n":17},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Confluence","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Google Workspace","optional":false},{"name":"IAM","optional":false},{"name":"Jira","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"n8n","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"OpenAI","optional":false},{"name":"OWASP","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Slack","optional":false},{"name":"Tool Use","optional":false},{"name":"Vertex AI","optional":false},{"name":"DLP","optional":true},{"name":"EU AI Act","optional":true},{"name":"ISO 27001","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LLM Guardrails","optional":true}],"status":"live","first_seen_at":"2026-10-16T09:57:36Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-16T23:27:40Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Capital.com is building out its internal platform capabilities, and AI is a growing part of that. The role combines architectural ownership with hands-on delivery: you will design, build, deploy and operate the platform, including its infrastructure and DevOps. Reporting to the Director of Product Security, you will set up this function as its first member and make the early technical decisions that the future team will build on.\nAs Platform Architect, you will own the architecture of the platform that more than 1,000 employees rely on, including their access to AI tools such as Anthropic Claude, OpenAI and future providers.\nResponsibilities:\nBuild the AI platform architecture: the reference design for how LLM capabilities are accessed, governed, monitored, and extended across the organisation.\n\nOwn every architectural decision for the AI platform, and document, justify, and stand behind each one.\n\nEvaluate and select new models, tools, and frameworks as the market moves.\n\nDeliver the platform as a service, so teams can move their agents into governed cloud infrastructure.\n\nGovern Anthropic (Claude API, Claude Code, Anthropic Enterprise), OpenAI, and future providers, covering API access controls, credential management, model version policy, cost allocation, and acceptable use standards.\n\nOwn technical relationships with Anthropic and OpenAI at the enterprise level.\n\nBuild cloud infrastructure for AI workloads on AWS and GCP: Bedrock, SageMaker, Vertex AI, Cloud Functions, and supporting services (S3, Cloud Storage, IAM, and monitoring on both platforms).\n\nDeploy and securely configure n8n, and build automation workflows connecting LLMs to Jira, Confluence, Slack, Google Workspace, HR systems, and proprietary data sources.\n\nDesign and secure MCP servers and gateways connecting AI agents to internal services.\n\nBuild Python integrations for AI-powered internal tooling: RAG pipelines, agent frameworks, prompt libraries, and internal AI assistants.\n\nDeliver hands-on: you write the code, build the workflows, and deploy the tooling. This isn't an advisory role.\n\nBuild data privacy and security architecture for LLM usage in a regulated environment, including prompt classification, output controls, and audit trails aligned with FCA, CySEC, ASIC, and DORA.\n\nBuild observability across the full stack: token consumption, cost per team, latency, error rates, and policy violations across cloud platforms and direct API providers.\n\nBuild an AI adoption framework of standards, patterns, and onboarding materials that let teams across Technology use AI safely and consistently.\n\nRun internal enablement through workshops, documentation, and direct support for teams moving from ad-hoc AI use to governed, repeatable processes.\n\nReport AI platform status, risks, and roadmap to Technology leadership\n\nRequirements:\n8+ years in engineering, with at least 2 years building LLM-based systems in production, not prototypes or POCs.\n\nComfort operating as the first person in a function: you set your own priorities, unblock yourself, and deliver without a team around you.\n\nProduction-grade Python: tooling that others depend on, not scripts you hand off.\n\nDeep, hands-on experience with the Anthropic and/or OpenAI APIs: function calling, tool use, streaming, RAG, prompt management, token optimisation, and model versioning.\n\nHands-on experience with agentic platforms, MCP servers, and MCP gateways, including designing flows between AI agents and internal services.\n\nn8n: deploying, securely configuring, and maintaining multi-step automation workflows at organisation scale.\n\nSolid AWS for AI workloads: Bedrock, SageMaker, Lambda, S3, IAM, and CloudWatch, deployed and operated in production.\n\nSolid GCP for AI workloads: Vertex AI, Cloud Functions, Cloud Storage, IAM, and Cloud Monitoring.\n\nHands-on DevOps capability to deploy and run what you build.\n\nArchitectural thinking: end-to-end system design, clear trade-off documentation, and the ability to defend decisions to senior stakeholders.\n\nSecurity engineering for what you build: secrets and credential management, key rotation, and least-privilege IAM across cloud and SaaS.\n\nData protection and auditability by design: classifying what data can reach which model and provider, controlling and logging prompts and outputs, and building audit trails that hold up to a regulator.\n\nFluency in the LLM threat surface, including prompt injection, data exfiltration through model outputs, insecure tool and agent use, and model supply-chain risk, with working knowledge of a recognised framework such as the OWASP LLM Top 10 or NIST AI RMF.\n\nNice to have:\nFintech, brokerage, or financial services background.\n\nDORA or ISO 27001:2022 knowledge as it applies to AI system risk.\n\nFamiliarity with the EU AI Act and other AI regulatory requirements, as well as AI-specific risk and governance standards such as NIST AI RMF or ISO/IEC 42001.\n\nLLM orchestration frameworks: LangChain, LlamaIndex, or similar.\n\nHands-on experience with LLM guardrail and DLP tooling: Bedrock Guardrails, Vertex AI safety filters, or prompt-firewall and PII-redaction tools.\n\nExperience building internal developer platforms or AI centres of excellence.\n\nAWS Solutions Architect Professional, Google Professional ML Engineer, or equivalent.","description_format":"text","description_chars":5296,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Bulgaria","iso":"BG","kind":"country"},{"name":"Cyprus","iso":"CY","kind":"country"},{"name":"Poland","iso":"PL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Online Brokerage & Trading Platforms","Forex & CFD Brokers"],"lifecycle":[{"event":"open","at":"2026-10-16T11:02:24Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":55,"reasons":["conf:2","win:early"],"computed_at":"2026-10-17T01:55:50Z"},"pay":null,"html_url":"https://alion.io/job/capital-com-platform-architect","json_url":"https://alion.io/job/capital-com-platform-architect.json","meta":{"generated_at":"2026-10-17T01:55:50Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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