AI Architect

Job Overview

We are seeking a dynamic and innovative AI Architect to lead the design, development, and implementation of cutting-edge artificial intelligence solutions across diverse enterprise environments. In this role, you will leverage your expertise in system architecture, cloud computing, and AI technologies to craft scalable, secure, and high-performance AI systems. Your leadership will drive the strategic integration of AI capabilities into our core products and services, fostering innovation and operational excellence. If you thrive in a fast-paced environment where creativity meets technical mastery, this opportunity is for you!

Responsibilities

• Design and develop comprehensive AI architectures that align with business goals and technical requirements, ensuring scalability and robustness.
• Lead the integration of AI models and algorithms into existing enterprise systems, utilizing RESTful APIs, microservices, and service-oriented architecture principles.
• Collaborate with cross-functional teams to gather requirements, translate them into technical specifications, and develop proof-of-concept prototypes.
• Oversee cloud-based deployment strategies utilizing platforms such as AWS, Azure, or Google Cloud to ensure optimal performance and security.
• Implement DevOps practices including CI/CD pipelines using Jenkins, Docker, Kubernetes, and version control systems like Git or SVN for seamless software delivery.
• Conduct system design reviews focusing on distributed systems, cloud infrastructure, scalability, and high availability.
• Stay abreast of emerging AI trends and technologies such as NLP, machine learning frameworks (TensorFlow, PyTorch), and big data tools (NoSQL databases like MongoDB or Cassandra).
• Define end-to-end technical architecture for AI/ML solutions: data flow, model integration, RAG/agentic patterns, APIs, and infrastructure
• Select the appropriate AI/ML approach for each use case (LLM vs. traditional ML, no-code/low-code vs. full-code) based on requirements, data sensitivity, performance needs, and budget
• Ensure architectures meet federal security and compliance requirements: NIST SP 800-53 control mapping, NIST AI Risk Management Framework alignment, and Authority to Operate (ATO) documentation support
• Design for scalability, reliability, and cost efficiency across federal cloud environments (AWS GovCloud, Azure Government, hybrid/on-prem)
• Establish MLOps/LLMOps practices — model versioning, monitoring, retraining triggers, and CI/CD for ML and generative AI pipelines
• Provide technical oversight, code/design review, and mentorship to AI Engineers and full stack developers implementing the architecture
• Evaluate and recommend AI platforms, frameworks, and tools (cloud AI services, vector databases, orchestration frameworks) for specific engagements
• Support proposal development and technical solutioning for new business opportunities, including technical risk and cost tradeoff analysis
• Own the AI system documentation package (architecture diagrams, data flow diagrams, security control mappings) required to support agency ATO processes

Skills

• Extensive experience with cloud computing platforms (AWS, Azure) and cloud architecture design for scalable AI solutions.
• Proficiency in programming languages including Python, JavaScript, C#, Java, and Perl; familiarity with frameworks such as Spring Boot or.NET Core.
• Strong understanding of system design principles for distributed systems, microservices architecture, and service-oriented architecture (SOA).
• Hands-on experience with NoSQL databases (MongoDB), relational databases (MySQL, Oracle), and data modeling techniques.
• Knowledge of web development technologies including HTML5, CSS3, Angular, ReactJS, Ember.js, Bootstrap for front-end integration.
• Familiarity with containerization tools like Docker and orchestration platforms such as Kubernetes for deployment automation.
• Experience implementing APIs using RESTful standards or SOAP; understanding of API management best practices.
• Solid grasp of SDLC methodologies including Agile software development practices like Scrum or Kanban.
• Expertise in system security protocols including identity & access management; experience with WebSphere or Weblogic is a plus.
• Ability to design scalable systems considering performance optimization and cost-efficiency in cloud environments.
• **Deep expertise in LLM/generative AI architecture: RAG pipeline de…