Senior Solution Architect AI Solutions PreSales

This person will lead the design of AI-led and AI-enabled enterprise solutions from sales qualification through contract award. Partnering with Sales and clients, the role will translate business requirements into scalable solution architectures and compelling RFP/proposal responses. The position is revenue-facing, with success measured by solution quality and conversion of opportunities into signed business. The architect will guide delivery teams post-award to ensure alignment between the proposed and delivered solution. Strong enterprise application/platform expertise is essential, with the ability to identify where AI creates genuine business value and where conventional solutions are more appropriate.

Key Responsibilities:

Advisory and Thought Partnership

• Serve as a principal technical consultant throughout the sales lifecycle, collaborating with stakeholders to refine business problems prior to architectural mapping.
• Evaluate client infrastructure, data maturity, and operational workflows to architect pragmatic and sustainable AI implementation roadmaps.
• Provide expert guidance on the functional utility and constraints of AI, distinguishing between high-value AI use cases and areas where traditional methods excel.
• Enhance the organization's market presence by contributing to executive briefings, industry workshops, and thought leadership collateral regarding AI in education.
• Prioritize organizational change readiness and stakeholder alignment as critical success factors, ensuring technical architectures are sequenced for successful adoption.

Pre-Sales Support and Lead Response

• Act as the lead technical authority for the sales organization on all high-potential enterprise opportunities.
• Provide technical qualification, comprehensive effort modeling, and conceptual solutioning for incoming qualified leads.
• Lead discovery sessions and deep-dive requirement gathering with prospective enterprise clients.
• Advise leadership on technical feasibility, risk profiles, and strategic differentiation to improve competitive win rates.

Proposal and RFP Development

• Develop high-quality technical content for RFPs, RFI responses, and detailed Statements of Work (SOWs).
• Deconstruct complex bid requirements to align organizational capabilities with client needs, identifying strategic build or partner opportunities.
• Produce sophisticated AI architecture visualizations, technical narratives, and operational assumptions for client-facing submissions.
• Define robust positions on data privacy, model governance, and ethical AI mitigation to satisfy rigorous procurement and security reviews.
• Collaborate across legal, finance, and delivery teams to ensure technical solutions remain consistent with commercial objectives and timelines.
• Optimize bid turnaround by maintaining a centralized repository of validated architectural patterns and solution templates.

Solution Design and Architecture

• Contextualize requirements within specific industry domains, including EdTech, publishing, Life Sciences, BFSI, and manufacturing.
• Architect modular, AI-centric enterprise solutions designed to solve business challenges within complex technical constraints.
• Deploy optimized AI methodologies, ranging from RAG and LLM applications to agentic workflows and traditional ML as required.
• Integrate rigorous evaluation frameworks, human-in-the-loop protocols, and safety guardrails as foundational elements of the system design.
• Establish comprehensive integration frameworks, data lineage, and infrastructure requirements for end-to-end delivery.
• Analyze buy-vs-build scenarios to recommend the most efficient and scalable deployment strategy.
• Quantify and articulate the trade-offs between accuracy, latency, and operational costs for AI-driven approaches.
• Engineer holistic enterprise ecosystems including non-functional requirements (SLAs, scalability, observability) and secure integrations with legacy systems (CRM, ERP, LMS) via robust API patterns.
• Harmonize traditional and AI technologies within a unified architecture to ensure optimal system performance and reliability.
• Generate standardized EA artifacts, including reference architectures and decision records, aligned with client data and cloud governance.
• Formulate Total Cost of Ownership (TCO) models, encompassing licensing, capacity planning, and scaling economics for AI solutions.

Prototyping and Demonstrations

• Develop high-impact proofs of concept (PoCs) and functional prototypes to demonstrate the tangible value of AI solutions.
• Deliver customized technical demonstrations that speak directly to the client's unique operational context and pain points.
• Iterate on architectural designs based on stakeholder feedback from prototype reviews to ensure final submission alignment.

Client Presentation and Stakeholder Engagement

• Present complex architectures to C-suite leadership, procurement committees, and specialized academic governing bodies.
• Champion technical strategies during bid reviews and provide evidence-based responses to technical clarifications.
• Address concerns regarding AI ethics, IP protection, and data security with technical depth and industry-specific insight.
• Calibrate technical communication to suit varied audiences, from business stakeholders to deep-technical and procurement specialists.

Qualifications & Experience

• Experience in Solution Architecture, Technical Pre-Sales, or Solution Engineering, with strong client-facing and revenue-linked exposure.
• Proven expertise architecting large-scale, mission-critical enterprise platforms, across both AI and non-AI solutions, with strong integration, API, cloud, data, security, IAM, and DevOps capabilities.
• Hands-on experience delivering production-grade AI solutions, including LLMs, RAG, agentic/multi-agent workflows, prompt/context engineering, evaluation, guardrails, and human oversight.
• Strong understanding of Responsible AI, privacy, IP, bias, transparency, and compliance, including SOC 2, ISO 27001, GDPR, DPDP, HIPAA/GxP, security, and data residency.
• Proven ability to lead technical proposals/RFPs, client-facing POCs/prototypes, multi-vendor bids, and advise senior stakeholders on AI strategy, adoption, and organizational readiness.
• Experience with enterprise learning technology including LMS/LXP, SCORM, xAPI, LTI, WCAG 2.2, and Section 508; exposure to academic/institutional governance is preferred.
• Excellent technical writing, presentations, stakeholder advisory, Agile/Scrum, and modern front-end/rapid AI prototyping skills, with public contributions to AI/learning technology preferred.
• Bachelors degree in CS/Engineering or equivalent; cloud certification (AWS/Azure/GCP), Scrum certification, and TOGAF/Enterprise Architecture certification or equivalent experience preferred.

Disclaimer: You must take the necessary steps to safeguard the integrity, security, and confidentiality of shared confidential information

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