Sr Solutions Engineer

Job Description

Job Description

Tekfortune is a fast-growing consulting firm specialized in permanent, contract & project-based staffing services for world s leading organizations in a broad range of industries. In this quickly changing economic landscape, virtual recruiting and remote work are critical for the future of work. To support the active project demands and skills gaps, our staffing experts can help you find the best job for you.

Position: Sr Solutions Engineer (1 position)
Location: Phoenix, AZ only (3 days onsite/2 remote)

12 month contract with potential to extend and/or convert FTE

Requirements:

• AI and automation expertise General knowledge of generative AI, agentic AI, and automation well enough to guide technical conversations and judge what's feasible.
• Use-case qualification - Assess AI ideas for value, data readiness, and feasibility, and prioritize them across a pipeline.
• Requirements translation - Turn loose business ideas into clear, actionable use cases for development teams.
• Stakeholder management Be a consultative partner who works well with senior leaders and builds alignment across teams.
• Governance and compliance - Risk, compliance, and AI governance standards in a regulated environment.

Position Summary
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, ensuring they are aligned to strategic priorities, enterprise standards, and delivery constraints. Within the AI Engagement & Transition pillar, this role focuses on structured intake and pre-sales of AI and agentic use-cases, including evaluating business value, data availability and readiness, tooling feasibility, and clarity of functional and non-functional requirements. In contrast to the Solution Engineer Lead role, which is more directly focused on leading the engagement approach and decomposing work for intake and transition activity, the Senior Solution Engineer role provides broader solution leadership across complex opportunities, helps shape target-state approaches, and is accountable for ensuring qualified use-cases are positioned for scalable, compliant, and production-ready delivery. This individual advocates and advances modern, governed solution delivery practices and evangelizes strong design, engineering, and organizational practices.

Key Responsibilities:
" Lead complex intake and qualification discussions for AI and automation use-cases across Network Services, helping stakeholders define target outcomes, scope, and value.
" Assess proposed use-cases for business value, strategic relevance, data availability and readiness, tooling feasibility, operational fit, and implementation complexity.
" Facilitate solution-driven discussions and help shape high-level approaches for qualified use-cases so they are positioned for efficient downstream design and delivery.
" Refine and document functional requirements, non-functional expectations, dependencies, assumptions, and risks needed for prioritization and transition into execution.
" Partner with business, engineering, architecture, product, data, and control stakeholders to ensure qualified use-cases align with enterprise standards and delivery constraints.
" Help maintain and shape a prioritized portfolio of AI and automation opportunities, balancing value, feasibility, reuse potential, and available capacity.
" Provide senior-level pre-sales engagement for use-cases by advising on feasibility, likely delivery approach, tooling suitability, and readiness for pilot or build activity.
" Contribute to intake methods, qualification criteria, templates, and governance-aligned engagement practices that improve consistency and decision quality.
" Support and guide more junior Solution Engineers and related contributors on use-case evaluation, requirements quality, stakeholder engagement, and structured solution framing.
" Participate in relevant steering, review, or community forums to improve consistency, drive reuse, and strengthen the operating model for AI use-case transition.
" Ensure qualified opportunities are positioned to meet governance, risk, compliance, and production-readiness expectations before transition into development or pilot execution. See attached JD for additional information.

Primary Skill
Others - Please specify
Secondary Skill

Tertiary Skill

Required Qualifications
" Strong 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, high-quality opportunities with clear outcomes and implementation paths.
" Advanced ability to evaluate business value, strategic fit, operational impact, and prioritization tradeoffs for proposed use-cases.
" Experience assessing data availability, data readiness, knowledge sources, and context dependencies required to support AI-enabled solutions.
" Strong understanding of tooling feasibility, enterprise platforms, integration patterns, operational constraints, and implementation dependencies.
" 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 or cross-domain initiatives.
" Strong stakeholder management and consulting skills, with the ability to engage senior business and technology leaders and build alignment across functions.
" Experience maintaining or influencing prioritized backlogs, intake pipelines, or use-case portfolios aligned to value and execution capacity.
" Strong written and verbal communication skills with the ability to communicate solution considerations, tradeoffs, and readiness to technical and non-technical audiences.
" Knowledge of Agile delivery practices and ability to connect early-stage qualification to downstream implementation, governance, and production readiness.
" Experience supporting or guiding more junior engineers and contributors on solution framing, requirements refinement, and intake quality.
" Familiarity with AI governance, model risk management, and approval considerations relevant to enterprise AI and agentic solutions.
" Experience working in a fast-paced and complex global environment with evolving priorities and cross-functional dependencies.
" Strong analytical thinking, structured problem solving, and sound decision-making judgment.

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