Sr. Partner Sales Engineer

About the role

The Sr. Partner Sales Engineer will serve as a technical and strategic lead for a focused portfolio of partners and partner-led opportunities across the Public Sector and U.S. South markets. This role combines partner practice development, enterprise presales, solution architecture, technical enablement, and hands-on opportunity execution.

Responsibilities

• Develop technical account plans for assigned partners based on their go-to-market priorities, industry strengths, delivery capabilities, target accounts, and services economics.
• Build trusted-advisor relationships with partner executives, practice leaders, solution architects, sales engineers, and other technical stakeholders.
• Assess partner readiness and potential, prioritizing investment toward partners capable of selling, building, supporting, and scaling repeatable customer outcomes.
• Align with alliance managers and field leadership on joint priorities, account mapping, coverage, and measurable success criteria.
• Lead discovery and architecture workshops that connect business and mission outcomes to AI-ready data, analytics, automation, governance, and deployment requirements.
• Design secure cloud, hybrid, and on-premises solution patterns across data platforms, enterprise applications, and modern AI and analytics environments.
• Guide partners on relevant AI, automation, analytics, workflow, and cloud capabilities while accurately distinguishing released functionality from preview or roadmap items.
• Develop joint architectures and integration patterns involving strategic cloud, data, and technology platforms.
• Support partner-led opportunities from discovery through technical close, including demonstrations, whiteboarding, solution design, objection handling, security reviews, and executive presentations.
• Structure proofs of concept and partner acceleration initiatives around defined customer sponsors, measurable problems, baselines, acceptance criteria, delivery ownership, and credible paths to production.
• Establish clear qualification, design, proof, and production milestones, resetting or stopping initiatives when customer demand, product fit, security, economics, or delivery ownership are not sufficiently validated.
• Capture reusable technical evidence, including reference architectures, demonstrations, customer proof points, lessons learned, and delivery handoffs.
• Partner with Public Sector sales and delivery teams to identify mission-critical opportunities across government operations, defense and intelligence, public health, finance, infrastructure, transportation, human services, and public safety.
• Translate agency priorities into measurable outcomes such as improved service delivery, stronger forecasting, resource optimization, faster response, improved data quality, and auditable decision-making.
• Address requirements related to secure data access, hybrid deployment, governance, lineage, regulatory compliance, accessibility, and responsible AI.
• Support partner-led account planning, capture activities, and technical responses for relevant procurement opportunities.
• Create role-based enablement for partner sellers, presales professionals, architects, and delivery consultants covering messaging, discovery, demonstrations, architecture, and implementation readiness.
• Coach partner technical teams through hands-on builds, certification pathways, technical win plans, and delivery-quality reviews.
• Develop scalable assets such as demonstration environments, solution blueprints, reusable workflows, industry playbooks, competitive guidance, and facilitator materials.
• Measure partner enablement through demonstrated technical capability and successful customer execution rather than activity volume alone.
• Bring structured partner and customer feedback to product and engineering teams, using evidence to influence priorities and closing the feedback loop with the ecosystem.
• Track technical milestones, partner readiness, risks, outcomes, and attribution while providing concise business and technical updates.
• Represent the organization at partner events, executive briefings, technical communities, and customer forums.

Qualifications

• 7+ years of relevant experience in enterprise presales, sales engineering, solution architecture, technical consulting, or a related field within data, analytics, automation, AI, enterprise software, or adjacent technologies.
• At least 3 years of direct experience working with partner ecosystems such as global or regional systems integrators, solution providers, distributors, ISVs, or hyperscalers.
• Demonstrated success developing partner technical capabilities and supporting partner-sourced or partner-led enterprise opportunities through technical close.
• Hands-on experience leading technical discovery, designing architectures, building compelling demonstrations, and defining outcome-based proofs of concept.
• Working knowledge of data preparation, analytics, workflow automation, governance, AI/ML, and agentic AI concepts.
• Familiarity with APIs, OAuth, MCP, LLM integration, human oversight, and related AI architecture concepts.
• Experience working with public cloud and modern data platforms such as AWS, Azure, Google Cloud, Snowflake, or Databricks, including hybrid and on-premises integration patterns.
• Practical proficiency with SQL and at least one relevant analytics or programming environment such as Alteryx, Python, or R.
• Strong executive presence and the ability to translate technical complexity into business, partner, and mission outcomes for C-suite, architecture, security, data, and business audiences.
• Strong commercial judgment, prioritization, written communication, and stakeholder-management skills.
• Ability to challenge weak qualification, unsupported assumptions, and ungrounded roadmap expectations while maintaining strong partner relationships.
• Ability and willingness to travel up to 40% based on territory and business needs.
• Experience supporting U.S. Public Sector agencies and the partner ecosystem serving them is preferred.
• Experience with Alteryx or comparable data and analytics platforms, with the ability to quickly develop expertise across cloud and enterprise modules, is preferred.
• Applied experience with generative AI or agentic architectures, including RAG, MCP-based tool use, prompt and context design, evaluation, guardrails, and responsible AI, is preferred.
• Experience creating partner practices, packaged offerings, reference architectures, marketplace propositions, or managed services is preferred.
• Cloud, data platform, architecture, security, or AI certifications relevant to the territory and partner portfolio are preferred.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline, or equivalent practical experience.