- Company Name
- Archigos Solutions
- Job Title
- AI Automation Lead/Architect
- Job Description
-
**Job Title:** AI Automation Lead / Solution Framing Lead
**Role Summary:**
Lead front‑door intake and discovery for AI, analytics, and automation initiatives, turning early ideas into well‑scoped, measurable, production‑ready problem statements. Drive stakeholder workshops, assess AI fit, define decision and workflow architecture (including human‑in‑the‑loop), and govern vendor solutions against security, data, and operational standards.
**Expactations:**
- Deliver consistent, executive‑ready artifacts (1‑3 pages) that enable delivery teams to move from concept to production.
- Maintain rigorous intake, feasibility, and risk screening processes.
- Ensure all solutions meet non‑functional, monitoring, and support requirements.
- Align stakeholders on realistic expectations, value hypotheses, and success criteria.
**Key Responsibilities:**
- Conduct intake calls and discovery workshops; clarify objectives, pain points, stakeholders, and desired outcomes.
- Perform AI/automation fit assessments; distinguish between automation, analytics, and GenAI use cases.
- Translate ideas into structured deliverables: problem statement, decision points, workflow steps, data inputs/outputs, HITL design, KPIs, and value cases.
- Govern vendor proposals using defined requirements, security, RBAC, and auditability criteria; prevent scope creep.
- Execute a repeatable early‑stage workflow: intake checklist, discovery facilitation, risk screen, data readiness assessment, MVP definition, roadmap, and handoff package.
- Produce concise deliverables: intake brief, current‑state process map, fit assessment, decision architecture, data readiness checklist, MVP scope with acceptance criteria, vendor evaluation rubric.
**Required Skills:**
- 8‑12+ years in Business Analysis, Product Analysis, Solution Consulting, or Digital Transformation with end‑to‑end discovery‑to‑delivery ownership.
- Proven track record delivering AI/automation solutions into production (operationalization, monitoring, change management, support).
- Deep knowledge of workflow automation (RPA/BPM), analytics/decision support, and GenAI/RAG patterns.
- Ability to define measurable outcomes: OKRs, baselines, benefits cases, value hypotheses, success criteria.
- Vendor management and governance experience: requirements definition, evaluation, security controls, scope management.
- Strong stakeholder leadership: workshop facilitation, executive alignment, clear communication of trade‑offs.
- Familiarity with data readiness assessment, data governance, RBAC, privacy/security constraints, and audit logging.
- Agile delivery, stage‑gate, and portfolio intake methodology experience.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Engineering, Business Administration, Data Science, or a related field (or equivalent professional experience).
- Preferred certifications: PMP, CBAP, PMI‑ACP, Certified RPA Developer, or AI/ML certification (e.g., Microsoft AI‑900, Google Cloud Professional Data Engineer).