AI Solution Architect @ Ework Group

AI Solution Architect @ Ework Group

Polsko

✔Must‑have skills:

• Leadership and ownership 
• Operates with high autonomy, bias to action, and accountability for outcomes. 
• Proven ability to align executives and guide cross‑functional teams without formal authority. 
• Communication and influence 
• Excellent written and verbal communication and meeting facilitation skills. 
• Translates technical topics (LLMs, safety, SOs) into business terms and tradeoffs. 
• Product and delivery thinking 
• Evidence‑driven decisions; comfort with A/B testing, canary rollouts, and ROI models. 
• Governance and security mindset 
• Practical understanding of data governance, privacy, and AI safety guardrails; policy‑as‑code. 
• Hands‑on AI systems integration 
• Experience integrating GenAI (LLMs/RAG/KG/agents) into real products with telemetry, guardrails, and rollback. 
• AIOps and reliability fundamentals 
• SLI/SLO design, error budgets, incident management, observability, CI/CD for prompts/policies/indexes. 
• Manufacturing/OT/IoT/Edge AI experience; familiarity with device data and shop‑floor constraints. 
• Microsoft Azure: Azure OpenAI, Cognitive Search, API Management, App Service/AKS, Functions, Event Hubs, Key Vault, Monitor; Azure ML or equivalent. 

✔Experience profile:

• 7–12+ years in software/AI product delivery with 3+ years leading cross‑functional initiatives. 
• Track record of shipping AI or data‑intensive systems to production in enterprise settings. 
• Demonstrated practice of Site Reliability Engineering (SRE)/AIOps concepts (SLOs, incident response, observability). 

? For our Client we are looking for AI Solution Architect ?

The project is new and the Client search for experienced Solution Architect who will be responsible for implementation of AI agent and review further needs to create the overall AI strategy with close cooperation with C-level stakeholders. You will cooperate with development team, but also you will act as Expert who will be responsible for making strategic decision on technologies and will have real impact on the strategy for systems. 

,[Co‑create AI vision, KPI tree, and prioritized use‑case portfolio with business leaders. , Translate strategy to a delivery roadmap and budget, with explicit risk and dependency plans. , Delivery leadership , Lead cross‑functional pods (data, platform, app, safety, SRE) from discovery through production. , Design A/B and canary rollout strategies; enforce guardrails and incident playbooks. , AI system engineering , Architect and guide implementation of LLM/RAG/agent solutions, including retrieval quality, prompt/policy engineering, guardrails, and evaluation harnesses. , Drive observability (tracing, safety counters, cost telemetry) and SLO compliance. , Governance and security , Stand up policy‑as‑code, model/prompt versioning, access controls, data residency, and vendor risk assessments. , Chair or collaborate with the governance board; run review gates. , Stakeholder engagement , Communicate simply and often; convert ambiguity into decisions; manage expectations. , Run demos, evidence‑based decisions, and post‑incident reviews. , Talent enablement , Mentor teams on AIOps/SRE practices; cultivate champions; reduce burden through automation. ] Requirements: AI, Microsoft Azure, solution architecture, GenAI, RAG, AI agent Tools: .

Kategorie

artificialIntelligence

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