• Lead technical discovery with client business, data, security and technology stakeholders; convert business priorities into qualified AI use cases, solution requirements and a practical delivery approach.
• Design secure, scalable enterprise architectures for generative AI, agentic AI, conversational AI, intelligent search, document intelligence and AI-enabled applications using the Microsoft cloud stack.
• Build working demonstrations, accelerators and proof-of-concepts using production-relevant patterns—not only mock-ups—to validate feasibility, user experience, integration and expected value.
• Own the technical workstream of RFPs, RFIs and proposals, including architecture, solution narrative, scope, assumptions, dependencies, non-functional requirements, effort estimates, bill of materials and delivery risks.
• Define RAG, grounding, tool-use, memory, orchestration, evaluation, observability and human-in-the-loop patterns appropriate to each use case.
• Assess model and platform choices across quality, latency, throughput, security, data residency, responsible AI and cost; explain the trade-offs clearly to both technical and executive audiences.
• Present solutions in workshops, solution reviews, demonstrations and bid presentations; respond credibly to detailed questions from enterprise architecture, cybersecurity and procurement teams.
• Work with account, industry and delivery teams to shape opportunities, identify reusable assets and position differentiators without overcommitting scope or capability.
• Support technical due diligence, implementation planning and handover after award, ensuring that proposal commitments are understood, feasible and traceable into delivery.
• Maintain current knowledge of Microsoft AI services, reference architectures, licensing and emerging agentic patterns, and turn that knowledge into reusable pre-sales assets.
• 7+ years of professional experience across software engineering, cloud architecture, AI/ML engineering or enterprise solution consulting.
• At least 3 years of hands-on experience specifically designing and building generative AI solutions using large language models, including enterprise RAG and/or AI agents.
• Demonstrable experience delivering AI or advanced analytics solutions beyond proof-of-concept stage, with a strong understanding of production engineering, security, monitoring and operational support.
• Strong hands-on development capability in Python and APIs/SDKs; experience with C#/.NET is advantageous.
• Deep understanding of LLM application patterns: prompt and context engineering, embeddings, vector and hybrid retrieval, tool/function calling, structured outputs, agent orchestration, evaluation and guardrails.
• Experience integrating AI solutions with enterprise applications, APIs, databases, document repositories and identity platforms.
• Strong knowledge of cloud security, Entra ID, managed identities, private networking, secrets management, role-based access control, data privacy and responsible AI controls.
• Proven client-facing experience in discovery, solution presentations, technical writing, estimation and proposal development for complex enterprise opportunities.
• Ability to produce clear architecture diagrams, sequence flows, assumptions, sizing models and implementation plans under bid deadlines.
• Excellent written and verbal English; able to challenge requirements constructively and communicate complex concepts without unnecessary jargon.