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Solution Architect
Luxoft
Poland
≈ 3,9 млн–6,2 млн ₽ · 43,7 тыс.–69,9 тыс. €
50 000 – 80 000 $
🏢 Офис
Middle
Полная занятость
Польша
Релокация
Описание вакансии
Project description
We are seeking a highly experienced Solution Architect to design, guide, and govern scalable software solutions across the organization—ranging from individual components to fully integrated enterprise platforms.
This role requires strong expertise in AWS cloud technologies, AI infrastructure, and advanced AI governance practices, ensuring solutions align with business strategy, security standards, and responsible AI policies.
Responsibilities
•Architecture & Solution Design
•Design end-to-end architectures spanning:
•Component-level services (microservices, APIs)
•Domain platforms
•Enterprise-wide ecosystems
•Define architecture patterns, standards, and reusable frameworks
•Translate business requirements into scalable and secure technical solutions
•Ensure interoperability across systems, data layers, AI services, and platforms
•Enterprise Architecture Strategy
•Develop and maintain enterprise architecture roadmaps
•Align IT strategy with business goals and digital transformation initiatives
•Establish governance models (TOGAF/SAFe or similar)
•Lead architecture review boards and technical decision-making processes
•Cloud Architecture (AWS)
•Architect and optimize cloud-native and hybrid solutions using AWS services
•Define cloud migration strategies and modernization approaches
•Ensure high availability, resiliency, cost optimization, and performance
•Implement Infrastructure-as-Code and automation best practices
•AI, Data & Intelligent Systems Architecture
•Design AI/ML infrastructure, pipelines, and enterprise integration patterns
•Architect solutions incorporating LLMs, generative AI, and intelligent agents
•Guide adoption of AI technologies within enterprise platforms and products
•Establish patterns for:
•RAG (Retrieval-Augmented Generation)
•Feature stores and data pipelines
•Model deployment, versioning, and scaling
•AI Governance, Observability & Control
•Define and implement enterprise AI governance frameworks covering:
•Responsible AI usage (fairness, bias mitigation, explainability)
•Data privacy, lineage, and compliance
•AI risk classification and policy enforcement
•Establish AI observability and monitoring capabilities, including:
•End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetry
•Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalent
•Metrics for model performance, drift, hallucination rates, and usage patterns
•Design and enforce agent governance and control mechanisms, including:
•Monitoring and auditing of autonomous and semi-autonomous AI agents
•Guardrails for agent behavior, tool usage, and decision boundaries
•Human-in-the-loop (HITL) workflows and escalation patterns
•Policy-based control over agent actions and integrations
•AI lifecycle governance, including:
•Model validation, approval workflows, and audit trails
•Continuous evaluation