Senior AI Solutions Architect

Quick Facts

• Lead enterprise AI solution design and delivery for clients and internally
• Bring AI from prototypes into production: secure, observable, reliable
• Work on orchestration layer, workflow decisions, evaluations, and costs

Description

You will provide technical leadership for enterprise AI implementations and for embedding AI into the software development process. The job emphasizes integrating AI with existing client systems so it’s safe, traceable, and dependable, and validating the approach in real code. You will become the main AI architect on selected projects after selecting an initial use case within the first two months.

Responsibilities

• Design an AI orchestration layer over existing architectures (APIs, events, legacy, on-prem systems)
• Decide when to use automation, controlled workflows, RAG, or agents, and defend choices to clients and engineers
• Own what moves from “demo” to “product”: identities/permissions, autonomy boundaries, idempotency, recovery from errors, AI Gateway, evaluations, tracing, and cost management
• Introduce AI into developer teams using shared project context and a knowledge base, plus skills/workflows for analysis, development, code review, testing, and measuring business impact
• Lead technical discovery and prepare architectural proposals, workflow/tool contracts, and reference implementations for critical parts (e.g., tool adapters or approval-based workflows)
• Guide AI fullstack developers, review key decisions, and help them deliver additional solution components independently

Requirements

• Experience as a software/solution architect or tech lead with practical AI expertise
• Proven ownership of enterprise AI architecture and delivery including integrations, identities, security, and production operations
• Hands-on contribution to AI apps/workflows with real data and tools; can explain evaluation, production issues, and costs after rollout
• Experience implementing AI ways of working in teams (shared context, skills, output verification, adoption)
• Proficiency with LLM APIs, structured outputs, tool calling, context management, and RAG
• API-first design and both synchronous and asynchronous integrations using events and cloud (prefer AWS; expect Azure at client sites)
• Ability to read, review, and write production code, ideally in TypeScript and Node.js
• Bonus: experience in banking or other security/audit-heavy environments; legacy modernization; platform engineering
• Communication skills in Czech or Slovak

Benefits

• Growth paths: go deeper as a hands-on expert impacting architecture, or take more project responsibility and share know-how
• Learning support: Udemy courses and internal workshops (including AWS certification prep)
• Access to domestic and international conferences; own stage at Qeetup
• English lessons and MultiSport card
• Sports events, teambuildings, and other Qest activities
• Karlín workspace with snacks and amenities; option to drop in anytime