AI Solution Architect
- Architect robust AI and data-driven solutions leveraging industry-leading technologies.
- Evaluate, select, and integrate commercial and open-source technologies, including Microsoft Azure services, Python environments, and LLM APIs (OpenAI, Anthropic, Perplexity, Meta).
- Lead design sessions and technical workshops with client stakeholders to define solution requirements and architecture.
- Document detailed architectural diagrams, technical specifications, and implementation plans.
- Provide hands-on code development and configuration of all architectural components, services, and products
- Provide ongoing architectural oversight throughout the project lifecycle, ensuring compliance with regulations (21 CFR Part 11, HIPAA).
- Establish and promote architectural best practices, standards, and governance models for AI and analytics development and deployment.
- Collaborate with clients to understand their business goals, AI maturity, and develop tailored strategies and solution roadmaps.
- Support business development efforts, including RFP responses, solution proposals, and client presentations.
- Continuously evaluate emerging AI trends, tools, and platforms to maintain solution effectiveness and innovation.
- Drive internal development of reusable frameworks, components, and accelerators for future projects.
- Contribute actively to the firm's AI strategy, thought leadership initiatives, and knowledge-sharing activities.
- Provide technical mentorship to development team members as needed.
- Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related technical discipline; Master’s degree preferred.
- 7+ years of experience in solution architecture and development.
- Prior experience in consulting, specifically in life sciences or healthcare environments.
- Proven track record of delivering complex projects in a client-facing or consulting capacity.
- Advanced expertise in Microsoft’s technology stack (Azure, SharePoint, Co-Pilot), containerization (Docker, Kubernetes), and retrieval-augmented generation (RAG).
- Familiarity with AI orchestration platforms such as Azure Machine Learning, Databricks, and MLflow.
- Deep understanding of AI/ML algorithms, frameworks, and lifecycle management (MLOps).
- Competence in security best practices (Azure Security Center, Azure Key Vault).
- Excellent interpersonal, communication, and consultative problem-solving skills.
- Certifications in cloud technologies (Azure) or relevant AI/ML certifications strongly preferred.
Please note: This application may be reviewed in part by automated systems to help identify qualified candidates.
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