Solutions Architect

Responsibilities

• Lead technical discovery sessions with federal customers and government stakeholders to scope requirements, define success criteria, and translate mission needs into actionable solution architectures.
• Design scalable, secure, and high-performance architectures that align with federal compliance standards, security requirements, and customer-specific needs.
• Build and deliver Proof of Concepts (POCs) and Minimum Viable Products (MVPs) to validate technical approaches and demonstrate solution value in government environments.
• Own end-to-end technical documentation, including architecture diagrams, technical specifications, integration guides, and deployment runbooks tailored for federal deployments.
• Drive technical alignment across sales, engineering, and product teams throughout the solution lifecycle.
• Guide solution implementation from initial design through deployment, ensuring smooth handoff to customer success and support teams.
• Evaluate and integrate third-party tools, APIs, and platforms into customer solutions to meet functional, non-functional, and security requirements.
• Contribute to internal knowledge bases, reference architectures, and reusable solution patterns for federal engagements.

Requirements

• Active Top Secret security clearance (required)
• Demonstrated experience in solution architecture, pre-sales engineering, or technical consulting with a track record of designing and delivering enterprise-grade systems for federal or defense customers.
• Thorough understanding of cloud computing platforms (AWS GovCloud, Google Cloud, Azure Government) and cloud-native design patterns in government environments.
• Strong proficiency in Python with experience building production-quality applications and automation.
• Expert-level understanding of system integration patterns, including RESTful and GraphQL APIs, webhooks, and event-driven architectures.
• Solid understanding of SQL and database operations (e.g., query optimization, schema design, transactions).
• Ability to lead technical discussions and present complex architectures to both technical and non-technical audiences, including government stakeholders.
• Baseline understanding of AI/ML concepts (e.g., ML workflows, data pipelines, NLP, or RAG) and data science engineering practices.
• Experience with orchestration frameworks, LLMs, or knowledge retrieval systems.
• Familiarity with MLOps practices, such as model versioning, deployment pipelines, experiment tracking, and model monitoring.
• Experience with FedRAMP, FISMA, or other federal compliance frameworks.
• Exposure to additional programming languages or technology stacks is a plus.
• Strong problem-solving skills with the ability to analyze ambiguous requirements and propose effective solutions.
• Experience with Agile methodologies and DevOps/CI-CD practices.
• Strong written and verbal communication skills, with an emphasis on technical documentation.
• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).