Senior Solution Engineer

Matlen Silver
Chandler, AZ, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$135,200.0 - $145,600.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Agile Methodology Artificial Intelligence Machine Learning Automation of Marketing Software Deployment Enterprise Application Integration Enterprise Software Applications System Availability Large Language Models Multi-Agent Systems Generative AI
+2 more
AI Platforms Virtual Agents

Job description

OverviewWe are seeking a Senior Solution Engineer to lead the qualification, shaping, and solution design of complex AI and automation initiatives across a large-scale enterprise environment. This role serves as the bridge between business stakeholders, architecture, engineering, data, governance, and delivery teams, helping transform high-level ideas into well-defined, actionable AI and automation opportunities. The ideal candidate has a strong background in solution engineering, consulting, enterprise architecture, AI use-case evaluation, and stakeholder engagement. This individual will assess business value, technical feasibility, data readiness, governance requirements, and operational considerations to ensure solutions are positioned for scalable and production-ready delivery. Responsibilities

  • Lead discovery, intake, and qualification discussions for AI, automation, and agentic AI initiatives.
  • Partner with business and technology stakeholders to define business outcomes, scope, success metrics, and value realization.
  • Evaluate use-cases for strategic alignment, business value, implementation complexity, and operational impact.
  • Assess data readiness, knowledge sources, integration requirements, and platform dependencies required for AI-enabled solutions.
  • Facilitate solution-focused discussions and develop high-level solution approaches for qualified opportunities.
  • Document functional requirements, non-functional requirements, assumptions, dependencies, risks, and constraints.
  • Collaborate with architecture, engineering, product, data, security, risk, and compliance teams to ensure alignment with enterprise standards.
  • Support portfolio prioritization efforts by balancing business value, feasibility, resource capacity, and reuse opportunities.
  • Provide solution consulting and pre-delivery guidance on tooling selection, implementation approaches, and readiness for pilot or production deployment.
  • Contribute to governance frameworks, intake processes, qualification methodologies, and engagement best practices.
  • Mentor junior solution engineers and assist with solution framing, stakeholder management, and requirements refinement.
  • Ensure opportunities are positioned to meet governance, risk, compliance, and production-readiness requirements prior to development.

Requirements

Do you have experience in Stakeholder relationship building?, * 8+ years of experience in Solution Engineering, Solution Architecture, Technical Consulting, Enterprise Architecture, or related roles.

  • Proven experience shaping and qualifying complex AI, automation, or enterprise technology initiatives.
  • Strong ability to translate ambiguous business problems into structured, actionable solution opportunities.
  • Experience evaluating business value, ROI, feasibility, prioritization, and implementation tradeoffs.
  • Strong understanding of AI/ML solutions, Generative AI, Agentic AI, automation platforms, and enterprise technology ecosystems.
  • Experience assessing data availability, data quality, knowledge sources, and readiness for AI implementations.
  • Knowledge of enterprise integration patterns, APIs, platform architectures, and solution dependencies.
  • Experience working within governance, risk, compliance, and regulated enterprise environments.
  • Strong stakeholder management skills with the ability to influence business leaders, architects, engineers, and product teams.
  • Experience working in Agile environments and supporting the transition from ideation through implementation.

Preferred Qualifications

  • Experience supporting AI strategy, AI governance, or AI transformation initiatives.
  • Familiarity with model risk management, AI compliance, and responsible AI practices.
  • Experience with enterprise AI platforms, LLMs, agent frameworks, or intelligent automation technologies.
  • Background in financial services, banking, telecommunications, or other highly regulated industries.
  • Experience managing intake pipelines, opportunity portfolios, or technology roadmaps.
  • Prior experience mentoring junior engineers, architects, or solution consultants.

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