Senior GenAI Solutions Architect

• Serving as a trusted, customer-facing technical advisor who champions GenAI and agentic solutions across IL2–IL7 environments, guiding customers through secure, cloud‑agnostic architectures. 
• Define and design solutions leveraging AWS and Azure GenAI services, lead technical workshops and demonstrations, and contribute to best practices and reference architectures for advanced deep learning and digital engineering within the DoD. 
• Stay current with advancements in GenAI, multi-agent systems, and aerospace-focused AI techniques is essential to driving mission success. 
• Serve as a trusted advisor, becoming an evangelist for GenAI solutions both within the company and customer facing roles. 
• Demonstrate deep technical expertise in cloud infrastructure development and deployments in a cloud-agnostic methodology, working alongside North Wind IT staff and infrastructure engineers to maintain capable and secure systems.
• Work with customers and teammates to define and architect solutions that leverage AWS GenAI services (Amazon Bedrock, Amazon SageMaker Studio, Amazon Titan Embeddings, etc.) to address their most critical challenges.
• Work with customers and teammates to define and architect solutions that leverage and integrate with Azure GenAI services (AI Studio, AI Foundry, etc.)
• Lead technical workshops and demonstrations with customers to showcase the capabilities of NorthWind's platform and AI technologies.
• Contribute to the development of best practices and reference architectures for GenAI in the DoD.
• Stay up-to-date on the latest advancements in GenAI and related technologies.

Qualifications:

• Strong foundation in cloud‑native architecture, deep learning, and Generative AI, with hands‑on experience designing and deploying secure solutions across IL2–IL7 environments.
• Bachelor’s degree in computer science or a related field, or equivalent experience.
• 5+ years of experience architecting and deploying cloud-based solutions.
• 3+ years of hands-on experience with machine learning technologies and frameworks (e.g., TensorFlow, PyTorch, MLFlow, etc.).
• Experience working with large datasets and data pipelines.
• Strong understanding of cloud security principles and best practices, especially IL4-7 and CMMC 2.
• Excellent communication, presentation, and interpersonal skills.

• Demonstrate expertise with AWS and Azure AI services, proficiency in developing agentic and multi‑agent systems, and a proven ability to translate complex mission requirements into scalable, production‑ready architectures.

• Master’s degree in computer science or a related field.
• Experience with developing and training Generative AI models and techniques (e.g., LLMs, diffusion models).
• Experience with Amazon SageMaker Studio and other AWS machine learning services.
• Experience with Azure AI and data ecosystem tools, including Azure AI Studio, Azure AI Foundry, Microsoft Fabric, and related Azure data lake, data pipeline, and MLOps services.
• Expertise designing or optimizing reduced‑order models, physics‑informed neural networks, or other advanced deep learning techniques for aerospace or defense engineering workloads.
• Experience working in the DoD or public sector.
• Active security clearance (e.g., Secret, Top Secret).
• AWS Certified Solutions Architect – Professional certification.
• Demonstrated commitment to staying current on emerging GenAI, digital engineering, and aerospace‑focused AI advancements.
• Demonstrated ability to lead technical workshops, influence stakeholders, and drive adoption of modern GenAI practices within complex DoD organizations.
• Familiarity with secure DevSecOps practices, containerization, and infrastructure-as-code workflows commonly used in defense cloud environments.

Desired Characteristics

• Thrives in a fast‑paced, agile environment and is comfortable working within a distributed, cross‑time zone team. 
• Actively engage on collaborative communication channels such as Slack, Teams, and Confluence, and are willing to jump into rapid‑response “tiger teams” when mission needs arise. 
• Demonstrates a strong willingness to learn, embraces iterative development, and consistently contributes to team success. 
• Think creatively to solve complex AI/ML challenges while adhering to North Wind’s security boundaries and DevSecOps principles, and they communicate effectively with engineers, program managers, and executive leadership alike.