Capital.com

Platform Architect

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SeniorHybryda·WarszawaFull-time

#459998·Dodano 9 dni temu·0

Źródło: Capital.com

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Tech Stack / Keywords

Python LLM Anthropic OpenAIn8nAWS GCPIAMDevOps

Firma i stanowisko

Capital.com is building out its internal platform capabilities with a growing focus on AI, serving more than 1,000 employees.

Wymagania

8+ years engineering experience with at least 2 years building production LLM-based systems.
Ability to operate independently as the first person in a function, setting priorities and delivering without a team.
Production-grade Python development skills.
Deep experience with Anthropic and/or OpenAI APIs including function calling, tool use, streaming, RAG, prompt management, token optimization, and model versioning.
Experience with agentic platforms, MCP servers, and gateways designing AI agent service flows.
Experience deploying and securing multi-step automation with n8n at organizational scale.
Strong AWS skills for AI workloads including Bedrock, SageMaker, Lambda, S3, IAM, and CloudWatch.
Strong GCP skills for AI workloads including Vertex AI, Cloud Functions, Cloud Storage, IAM, and Cloud Monitoring.
Hands-on DevOps capability for deployment and operation.
Architectural thinking with end-to-end design, trade-off documentation, and ability to defend decisions.
Security engineering including secrets management, key rotation, and least-privilege IAM.
Data protection and auditability by design including classification, controls, logging, and audit trails.
Knowledge of LLM threat surfaces and frameworks such as OWASP LLM Top 10 or NIST AI RMF.

Obowiązki

Build the AI platform architecture including access, governance, monitoring, and extension of LLM capabilities.
Own architectural decisions for the AI platform and provide documentation and justification.
Evaluate and select new models, tools, and frameworks.
Deliver the platform as a service for teams to deploy agents into governed cloud infrastructure.
Govern API access, credential management, model version policies, cost allocation, and use standards for Anthropic, OpenAI, and future providers.
Manage technical relationships with Anthropic and OpenAI.
Build cloud infrastructure for AI workloads on AWS and GCP including Bedrock, SageMaker, Vertex AI, Cloud Functions, S3, Cloud Storage, IAM, and monitoring.
Deploy and securely configure n8n, build automation workflows connecting LLMs to Jira, Confluence, Slack, Google Workspace, HR systems, and proprietary data.
Design and secure MCP servers and gateways for AI agent connections.
Build Python integrations for AI tooling including RAG pipelines, agent frameworks, prompt libraries, and internal AI assistants.
Write code, build workflows, and deploy tooling hands-on.
Build data privacy and security architecture for LLM usage complying with FCA, CySEC, ASIC, and DORA regulations.
Build observability tools for token consumption, costs, latency, errors, and policy violations.
Develop an AI adoption framework with standards, patterns, and onboarding materials.
Conduct internal enablement through workshops, documentation, and direct team support.
Report AI platform status, risks, and roadmap to Technology leadership.

Benefity

Hybrid work arrangement.

Capital.com

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