Fujitsu
Principal Solution Architect (AI Systems Lead)
We are seeking a self‑driven AI Systems Lead to own vision‑to‑execution for enterprise AI initiatives, with a hands‑on focus on GenAI integration, security, and governance. You will define the AI vision with business stakeholders, translate it into an actionable roadmap, and lead cross‑functional delivery across data, platform, apps, and operations. This role blends leadership, product thinking, and deep practical execution across AIOps and modern AI system engineering (LLMs, RAG, agents, knowledge graphs). Ideal candidates have strong soft skills, are proactive and independent, and can operate in complex enterprise environments (manufacturing/OT/IoT preferred).
Responsibilities
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.
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.
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.
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.
Communicate simply and often; convert ambiguity into decisions; manage expectations.
Mentor teams on AIOps/SRE practices; cultivate champions; reduce burden through automation.
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.
Excellent written and verbal communication and meeting facilitation skills.
Translates technical topics (LLMs, safety, SOs) into business terms and tradeoffs.
Evidence‑driven decisions; comfort with A/B testing, canary rollouts, and ROI models.
Practical understanding of data governance, privacy, and AI safety guardrails; policy‑as‑code.
Experience integrating GenAI (LLMs/RAG/KG/agents) into real products with telemetry, guardrails, and rollback.
Manufacturing/OT/IoT/Edge AI experience; familiarity with device data and shop‑floor constraints.
SAP ecosystem awareness (SAP/S4H processes and integration points for AI governance).
Knowledge graphs/ontologies, hybrid retrieval (vector + keyword), embeddings, data contracts.
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).
Job Details
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Consulting
Industries: IT Services and IT Consulting
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Responsibilities
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.
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.
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.
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.
Communicate simply and often; convert ambiguity into decisions; manage expectations.
Mentor teams on AIOps/SRE practices; cultivate champions; reduce burden through automation.
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.
Excellent written and verbal communication and meeting facilitation skills.
Translates technical topics (LLMs, safety, SOs) into business terms and tradeoffs.
Evidence‑driven decisions; comfort with A/B testing, canary rollouts, and ROI models.
Practical understanding of data governance, privacy, and AI safety guardrails; policy‑as‑code.
Experience integrating GenAI (LLMs/RAG/KG/agents) into real products with telemetry, guardrails, and rollback.
Manufacturing/OT/IoT/Edge AI experience; familiarity with device data and shop‑floor constraints.
SAP ecosystem awareness (SAP/S4H processes and integration points for AI governance).
Knowledge graphs/ontologies, hybrid retrieval (vector + keyword), embeddings, data contracts.
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).
Job Details
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Consulting
Industries: IT Services and IT Consulting
#J-18808-Ljbffr