AI Architect

Data Science UA is a service company with deep expertise in AI and Data Science. Our story began in 2016 with the first Data Science UA Conference in Kyiv, and since then we've built one of the largest AI communities in Europe.

About the role:
We are looking for an AI Architect who will lead the architecture track of an enterprise AI transformation programme for a large Salesforce consulting client. The client is redesigning how the whole company builds and delivers: a centralized AI platform, an enterprise knowledge base, and an AI-native software delivery lifecycle across their Salesforce Core and Commerce Cloud practices. You own the sequence of design decisions. The client's internal teams have already generated ideas and prototypes; your job is to step back with them, define vision, objectives and constraints, then guide process re-engineering, solution architecture and tooling choices before implementation starts. You will work with the client's AI Strategy Board, their Enterprise AI Architecture Lead, and technical leads from each practice, and you represent Data Science UA as the architecture authority in the room.

Responsibilities:
- Lead architecture discussions across three parallel workstreams: Enterprise AI Architecture & Infrastructure, Enterprise AI Knowledge Base, and AI-Native Engineering (SDLC redesign);
- Design the target enterprise AI architecture: centralized AI platform and UI, data layer, model and tooling strategy, orchestration, and AI governance;
- Shape the Enterprise Knowledge Platform ("institutional brain"): ingestion, taxonomy, retrieval architecture, access control, integration with Confluence, Jira and Slack;
- Redesign the SDLC for Salesforce Core (CRM and integration) and Commerce Cloud (B2C, marketplaces) delivery teams: where AI agents fit, which stages change, what tooling supports them (coding agents, Jira-to-PR automation, code review agents);
- Facilitate design workshops with client technical leads and solution architects; drive decisions to written conclusions;
- Produce the key deliverables per workstream: solution architecture documents, capability maps, tooling recommendations, implementation roadmaps;
- Define required capabilities and phasing so DSUA engineering can execute against a clear plan;
- Set AI governance guardrails: model selection policy, data handling, evaluation, cost control.

Requirements:
- 7+ years in software architecture, 3+ of them designing systems at enterprise scale (multi-team, multi-system, with real governance constraints);
- Hands-on experience architecting LLM-based systems in production: RAG pipelines, agent orchestration, evaluation, cost and latency budgets;
- Experience designing knowledge management or enterprise search platforms, or deep familiarity with retrieval architecture;
- Working knowledge of the modern AI engineering stack: Claude / GPT-class models, Bedrock or equivalent cloud AI services, vector stores, orchestration frameworks, coding agents (Cursor, Claude Code or similar);
- Strong grasp of SDLC and delivery processes in consulting or outsourcing organizations; you can talk to a Head of Delivery about throughput and quality, not just to engineers about embeddings;
- Ability to run architecture workshops with senior client stakeholders in English (C1+), keep discussions on sequence, and turn debate into documented decisions;
- Experience producing architecture deliverables that non-architects act on: diagrams, ADRs, roadmaps.

Nice to have:
- Salesforce ecosystem exposure: Core platform, Commerce Cloud, Agentforce, or delivery experience in a Salesforce partner;
- AI governance frameworks in regulated or large-enterprise contexts;
- Prior consulting or client-facing lead role at an outsourcing company;
- Experience introducing AI tooling into engineering organizations and measuring adoption.

What we offer:
- Architecture ownership of a flagship enterprise AI programme with direct access to the client's C-level and AI Strategy Board;
- Small senior team, no internal bureaucracy; your decisions ship;
- Competitive compensation tied to seniority and engagement scope;
- Remote work, flexible hours with overlap for client workshops (EU time zones);
- Paid professional development and access to frontier-model tooling budgets.