We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact.
We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in.
We are a well-funded, early-stage startup hiring a Head of AI Solutions Engineering to build and lead our post-sales solution engineering organization. Reporting into COO, you will own technical execution from customer kickoff through design, integration, go-live, optimization, and expansion, leading a growing team across the US, Europe, and MEA.
This is a hands-on, customer-facing leadership role. Your team embeds with our customers’ operations, business functions and IT, solves the hardest technical and workflow challenges, and builds production AI agents that customers can trust and scale. Your mandate is simple: turn ambitious enterprise AI programs into repeatable, high-quality operational outcomes.
Your Impact
Enterprise Delivery & Production Success
Own post-sales solution delivery from implementation planning and paid pilots through production rollout, stabilization, and continuous optimization, with clear accountability for quality and speed to value.
Turn complex operational processes into well-scoped technical plans, success criteria, milestones, and production-ready architectures across business units and systems.
Establish disciplined testing, release management, monitoring, incident response, and escalation practices for business-critical AI workflows.
Solution Architecture, Integrations & Agent Reliability
Lead architecture and integrations with enterprise platforms such as SAP, Oracle, Workday, ServiceNow, email, documents, and customer data environments.
Set the standard for AI agent quality: evaluations, accuracy, observability, exception handling, human oversight, security, and ongoing performance improvement.
Remain genuinely hands-on when needed, diagnosing model behavior, context issues, APIs, data pipelines, and complex integration failures alongside the team.
Adoption, Value Realization & Expansion
Partner with Account Management and Customer Success to grow agent utilization, operational adoption, measurable customer value, and multi-use-case deployment.
Enable customer technical teams and builders to scale confidently through managed, hybrid, and self-service delivery models.
Turn early wins into reusable solutions and repeatable patterns that accelerate the next workflow, business unit, and customer.
Build & Lead a World-Class SE Organization
Recruit, coach, and scale exceptional post-sales Solutions Engineers, creating a culture of technical rigor, ownership, urgency, and customer empathy.
Build playbooks, reference architectures, implementation standards, delivery metrics, and team operating rhythms that improve predictability and throughput.
Manage capacity, priorities, and senior technical coverage across strategic enterprise accounts while developing future leaders.
Executive Partnership, Product & Ecosystem
Serve as the senior technical sponsor for strategic enterprise customers, building trust with IT, operations, and executive stakeholders through complex deployments.
Translate recurring field challenges into actionable priorities for our Product and R&D, helping improve platform reliability, integrations, and scalability.
Establish technical enablement and quality standards for implementation partners as the delivery ecosystem expands.
What It Takes
7+ years in customer-facing technical roles, including 5+ years building or leading post-sales Solutions Engineering, Forward Deployed Engineering, technical Professional Services, or similar teams.
Strong hands-on skills in Python and/or JavaScript/TypeScript, APIs, cloud environments, enterprise architecture, and system integration. You can still build and debug, not just review.
Real-world experience delivering Automation/Agentic-AI/LLM systems into production, including agent orchestration, evaluations, monitoring, failure modes, and human-in-the-loop workflows.
A track record of navigating enterprise complexity: security and compliance, data readiness, cross-functional dependencies, change management, and operational rollout.
Executive presence, excellent communication, and the ability to translate naturally between business outcomes and deep technical details.
A builder’s mindset and the judgment to balance speed with production quality in an early-stage company. Exposure to finance, procurement, supply chain, or enterprise operations is a plus.