Senior Manager - Solution 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:
As the Senior Manager – Solution Engineering (AI Solutions) at Inception, you will be the senior technical authority shaping, validating, and de-risking enterprise AI solutions across our most strategic customer engagements. Reporting to the Senior Director – Solution Engineering, this is a hands-on individual contributor role where you will lead AI solution design end-to-end , from discovery and architecture through to rapid prototyping and bringing together Generative AI, Agentic AI, Machine Learning, RAG, and Conversational AI capabilities into compelling, outcome-led solutions.
The opportunity
This role is ideal for a senior solution engineer or AI-focused architect who thrives on complex problems, enjoys moving from ambiguity to clarity, and can translate cutting-edge AI capabilities into credible, executive-ready narratives. You will not manage a team directly, but you will set the technical bar, mentor peers, influence product direction, and act as a trusted advisor to customers evaluating AI-first transformation.
Responsibilities:
AI Solution Design & Architecture
- Own end-to-end AI solution design for enterprise engagements, spanning Generative AI, Agentic AI, RAG, Machine Learning, and Conversational AI.
- Define high-level architectures, reference patterns, and solution blueprints that integrate Inception products with bespoke AI components and customer systems.
- Make pragmatic architectural trade-offs across performance, cost, latency, security, and responsible AI guardrails.
- Drive rapid prototyping and Minimum Loveable Prototypes (MLPs) to validate feasibility, value, and direction before full delivery investments.
Pre-Sales Solution Engineering
- Lead technical discovery and AI envisioning sessions to uncover customer goals, constraints, and AI-first transformation opportunities.
- Translate complex AI capabilities into clear, compelling solution narratives tailored to each customer context.
- Provide senior technical leadership on RFP responses, client workshops, and proofs-of-concept.
Customer Engagement & Thought Leadership
- Act as a trusted technical advisor to CxO and board-level stakeholders across strategic accounts.
- Deliver high-impact solution presentations, live demos, and executive briefings that build confidence in proposed AI solutions.
- Represent Inception’s AI vision externally, with credibility, clarity, and differentiation.
Cross-Functional Collaboration
- Partner with sales, product managers, applied science, and engineering leads to influence product roadmap based on real customer signals.
- Coordinate with applied science to validate model feasibility, performance, and scalability of proposed AI solutions.
- Ensure smooth handover from pre-sales to delivery teams during project kickoffs.
Practice Building & Mentorship
- Define reusable templates, design patterns, and AI reference architectures to standardise and scale the solutioning process.
- Mentor and coach Solution Engineers, raising the team’s capability in AI solutioning and rapid validation.
- Contribute to KPIs that measure pre-sales success such as win rate, deal velocity, and prototype-to-MVP conversion.
Qualifications:
Skills and attributes for success
- Deep conceptual and hands-on understanding of modern AI solution architectures – LLMs, RAG, vector databases, knowledge graphs, prompt engineering, fine-tuning, and agentic systems.
- Strong experience in technology consulting, solution engineering, technical pre-sales, or solution architecture roles.
- Ability to reason about system behaviour, cost, performance, and risk across AI components.
- Proven ability to prototype AI workflows quickly and pragmatically to validate ideas.
- Ability to simplify complex technical ideas for executive and business stakeholders.
- Collaborative, customer-first mindset with a bias for action and learning.
To qualify for the role you must have
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s preferred).
- 14+ years of experience in technical pre-sales, solution architecture, or consulting roles, with meaningful exposure to AI, cloud, or SaaS.
- Hands-on experience designing large-scale enterprise AI solutions – including at least one production-grade GenAI or ML solution.
- Experience in at least one industry: Retail, FSI, Telco, Software Product, or Public Sector/National Security.
- Experience working with commercial and delivery teams to support the full solution lifecycle.
Ideally, you’ll also have
- Experience with Agentic AI orchestrators, LLMOps, and responsible AI frameworks.
- Hands-on exposure to Azure AI platforms and hybrid / air-gapped deployments.
- Prior involvement in building solution frameworks, accelerators, or reusable technical assets.
- Certifications such as Azure Solutions Architect, Azure AI Engineer, or TOGAF.
- A business administration qualification.