AI Solutions Engineer
Apex Systems Inc
AI Solutions Engineer
Location: Chandler, Arizona (Hybrid) Role Overview This role is responsible for leading complex use-case shaping, qualification, and solution design activities that enable AI and automation outcomes across Network Services. The individual in this role works across business, engineering, architecture, and control stakeholders to assess and refine high-value use-case opportunities. This position focuses on the structured intake and pre-sales of AI and agentic use-cases, including the evaluation of business value, data availability, and tooling feasibility to ensure solutions are positioned for scalable, compliant, and production-ready delivery. Key Responsibilities- Lead complex intake and qualification discussions for AI and automation use-cases, helping stakeholders define target outcomes and scope.
- Assess proposed use-cases for business value, strategic relevance, data readiness, tooling feasibility, operational fit, and implementation complexity.
- Facilitate solution-driven discussions and help shape high-level approaches for qualified use-cases.
- Refine and document functional requirements, non-functional expectations, dependencies, assumptions, and risks for prioritization.
- Partner with business, engineering, architecture, product, data, and control stakeholders to ensure alignment with enterprise standards.
- Help maintain and shape a prioritized portfolio of AI and automation opportunities.
- Provide senior-level pre-sales engagement for use-cases by advising on feasibility, delivery approach, and tooling suitability.
- Contribute to intake methods, qualification criteria, and governance-aligned engagement practices.
- Support and guide more junior Solution Engineers on use-case evaluation and requirements quality.
- Ensure qualified opportunities are positioned to meet governance, risk, compliance, and production-readiness expectations.
- Experience shaping and qualifying complex AI, automation, or technology use-cases across multiple business and technology stakeholders.
- Demonstrated ability to lead solution-driven discussions and refine ambiguous ideas into actionable opportunities.
- Ability to evaluate business value, strategic fit, operational impact, and prioritization tradeoffs for proposed use-cases.
- Experience assessing data availability, data readiness, and knowledge sources required to support AI-enabled solutions.
- Understanding of tooling feasibility, enterprise platforms, integration patterns, and operational constraints.
- Working knowledge of enterprise architecture standards, solution governance, risk controls, and compliance requirements in regulated delivery environments.
- Experience contributing to complex solution design, architecture shaping, and readiness decisions for large initiatives.
- Stakeholder management and consulting skills, with the ability to engage senior business and technology leaders.
- Experience maintaining or influencing prioritized backlogs or use-case portfolios.
- Written and verbal communication skills to articulate solution considerations to technical and non-technical audiences.
- Knowledge of Agile delivery practices and ability to connect early-stage qualification to downstream implementation.
- Familiarity with AI governance, model risk management, and approval considerations relevant to enterprise AI solutions.
- Experience working in a complex global environment with evolving priorities.
- Analytical thinking, structured problem solving, and decision-making judgment.
- Machine Learning
- QA Automation
- Robotic Process Automation
Vacancy posted 4 days ago
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