About the Role / About the Job
In this role, you will lead technical discovery with client stakeholders in business, data, security, and technology. Your focus will be on converting business priorities into qualified AI use cases, developing solution requirements, and implementing a practical approach for delivery. You will design secure and scalable enterprise architectures that encompass generative AI, agentic AI, conversational AI, intelligent search, document intelligence, and AI-enabled applications utilizing the Microsoft cloud stack.
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Responsibilities
- Lead technical discovery sessions with stakeholders and convert business needs into effective AI use cases.
- Design secure, scalable architectures for various AI implementations, including generative AI and conversational AI.
- Build working demonstrations, accelerators, and proof-of-concepts using production-relevant patterns to validate feasibility and user experience.
- Manage the technical aspects of RFPs, RFIs, and proposals, detailing architecture, solution narratives, scope, assumptions, and delivery risks.
- Define and assess patterns such as RAG, grounding, memory, and orchestration tailored to each use case.
- Evaluate AI model and platform options by analyzing quality, latency, security, and cost, and communicate trade-offs to technical and executive audiences.
- Present solutions during workshops, reviews, and bid presentations, addressing queries from architecture, cybersecurity, and procurement teams.
- Collaborate with account and delivery teams to shape opportunities and identify reusable assets while managing project scope effectively.
- Support technical due diligence and implementation planning, ensuring proposal commitments are actionable and traceable into delivery.
- Stay up to date on Microsoft AI services, reference architectures, and emerging patterns to develop reusable pre-sales tools.
Qualifications
- 7+ years of professional experience in software engineering, cloud architecture, AI/ML engineering, or enterprise solution consulting.
- At least 3 years of hands-on experience in designing and building generative AI solutions using large language models.
- Proven experience in delivering AI or advanced analytics solutions beyond the proof-of-concept stage, specifically in production engineering and operational support.
- Strong development skills in Python and APIs/SDKs; experience with C#/.NET is considered advantageous.
- In-depth understanding of LLM application patterns including prompt engineering, embeddings, and vector retrieval.
- Experience integrating AI solutions with enterprise applications and platforms such as APIs, databases, and identity services.
- Knowledge of cloud security, Entra ID, role-based access control, and responsible AI controls.
- Client-facing experience in discovery, solutions presentations, technical writing, and proposal development.
- Ability to produce architecture diagrams, implementation plans, and sizing models under tight deadlines.
- Excellent written and verbal English communication skills, with the ability to explain complex concepts clearly.
