Vice President - Solutions Engineering
Inception, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inceptionai.ai
Overview:
We are looking for a VP of Solutions Engineering to lead the technical function that connects Inception42’s AI products, platform capabilities, and applied science work to real customer environments. This role exists to make sure strategic customers can understand, evaluate, deploy, and scale Inception42’s AI systems with technical clarity and operational confidence.
You will work closely with Product, Applied Science, Engineering, Delivery & Commercial to shape solution strategy, guide technical engagement with customers, and turn complex requirements into executable architectures. The role involves leading a senior solutions engineering team, setting technical standards for customer-facing work, and ensuring Inception42’s solutions are positioned, designed, and deployed with the rigor required for enterprise and national-scale environments.
Responsibilities:
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Lead the Solutions Engineering function across Inception42’s AI product and platform portfolio, setting the operating model, technical standards, and execution rhythm for customer-facing technical work.
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Own technical solution strategy for strategic customer engagements, from discovery and architecture through validation, deployment planning, and production readiness.
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Partner with Commercial teams to qualify opportunities, shape technical narratives, manage solution complexity, and ensure commitments are grounded in product capability and delivery reality.
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Translate customer requirements, operational constraints, data environments, security needs, and integration patterns into clear solution architectures and implementation paths.
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Work closely with Product and Engineering to feed customer requirements, deployment learnings, product gaps, and technical blockers into roadmap decisions.
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Collaborate with Applied Science teams to explain AI capabilities, model behavior, evaluation approaches, constraints, and trade-offs in ways that are technically accurate and decision-ready.
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Build repeatable mechanisms for demos, proofs of concept, technical workshops, solution design reviews, reference architectures, and deployment handoffs.
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Establish high standards for technical documentation, architecture artifacts, customer-facing materials, validation plans, and solution readiness gates.
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Lead and develop a team of solutions engineers and architects with strong technical judgment, customer credibility, and execution discipline.
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Drive alignment across product, engineering, delivery, security, legal, and customer stakeholders when requirements, timelines, risk, or architecture decisions need clear resolution.
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Improve the quality and repeatability of solution deployment by identifying patterns across customers, reducing bespoke work, and turning field learnings into productized capabilities.
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Represent Inception42 in senior customer and partner conversations where technical depth, product judgment, and deployment credibility are required.
Qualifications:
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Senior leadership experience in solutions engineering, sales engineering, customer engineering, solution architecture, technical field engineering, or enterprise AI/product deployment.
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Strong technical depth across AI products, software architecture, data platforms, APIs, cloud infrastructure, security, integration patterns, and production deployment environments.
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Proven ability to lead customer-facing technical teams that operate across discovery, architecture, demos, proof of concept execution, validation, and production handoff.
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Experience working with complex enterprise or national-scale customers where reliability, security, data governance, procurement complexity, and stakeholder alignment matter.
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Strong product judgment, with the ability to distinguish between customer-specific asks, roadmap-worthy patterns, and delivery risks.
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Ability to communicate clearly with executives, engineering teams, applied scientists, commercial teams, and customer technical stakeholders.
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Strong systems thinking, with the ability to connect product capability, customer workflows, technical architecture, delivery effort, operational readiness, and business value.
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Experience building operating models, technical standards, team structures, and repeatable processes for scaling a solutions engineering function.
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High ownership mindset, strong execution discipline, and comfort making decisions in ambiguous, high-stakes environments.
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Experience with AI-native products, LLM applications, agentic systems, RAG architectures, MLOps, model evaluation, or enterprise AI platforms.
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Experience with private cloud, hybrid cloud, on-prem deployment, Kubernetes/OpenShift, observability, identity, access control, or secure integration patterns.