Level

G42

Senior Manager - Solution Engineering

AI in this role

prompt-engineeringragfine-tuningai-safety

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.

Inception42 is building AI systems designed for practical deployment at scale — across industries, infrastructure, and national-level initiatives.

If you want to work close to both advanced AI capability and real-world execution, we’d like to hear from you.

How we rate this

Senior Manager - Solution Engineering at G42 rates 77 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGFine TuningAI Safety

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How do you think about the risk of an AI system in this kind of role failing silently?
  5. Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, RAG, Fine Tuning, and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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