Pre-Sales AI Architect

Key Responsibilities

• Shape and Scope AI Solutions in Response to Client Needs
• Engage with client stakeholders to uncover pain points, business drivers, and opportunities for AI-powered transformation.
• Conduct discovery sessions and assessments to define business requirements and align them with AI use cases.
• Lead early scoping activities, including defining delivery phases, resource profiles, timelines, assumptions, and risks for proposed AI projects.
• Design and Propose AI Architectures
• Translate client requirements into scalable, cloud-based AI architectures that balance technical feasibility, business value, and delivery risk.
• Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity.
• Collaborate with delivery and engineering leads to validate feasibility, identify dependencies, and align design with execution capability.
• Write and Lead AI Bid Responses
• Own the technical response for AI-related RFPs, RFIs, and procurement tenders, including:
• Detailed solution overviews and architecture descriptions
• Technical narratives and approach justification
• Delivery methodology and project structure
• Clear scope, assumptions, estimates, and risk management
• Craft persuasive, well-structured bid content that highlights our expertise, solution differentiation, and alignment with tender requirements.
• Act as the technical conscience of the bid, balancing ambition with deliverability.
• Articulate Value, Outcomes, and Innovation
• Demonstrate how proposed AI solutions will improve business performance, reduce costs, or unlock new capabilities.
• Present complex technical solutions in simple, compelling terms to both technical and non-technical stakeholders.
• Highlight innovation opportunities and ensure proposals showcase thought leadership and credibility.

Qualifications

• Proven experience in pre-sales, tender response writing, or client-facing architecture roles involving AI, data science, or analytics.
• Demonstrated ability to write high-quality bid responses for complex technology or AI solution tenders.
• Strong capability to scope AI/ML delivery work, including estimating effort, planning phases, and defining delivery models.
• Able to elicit business needs and convert them into AI/ML solution designs in cloud environments (Azure, AWS, or GCP).
• Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search.
• Experience designing AI solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face.
• Able to develop architecture artefacts (e.g., HLDs), technical narratives, effort estimates, and proposal content.
• Exceptional storytelling, writing, and presentation skills; able to build confidence with senior business and technical stakeholders.
• Experience working in bid teams or alongside account executives, ideally within a consultancy, systems integrator, or AI solution provider.
• Understanding of data governance, security, and ethical AI practices.
• Ability to adapt solutions across multiple sectors (e.g., public sector, utilities, finance, health) is a strong advantage.