AI Architect

Saxon Global•Fairfax, VA

19h

About The Position

The AI Architect will be responsible for defining and implementing the AI strategy for the program, ensuring alignment with business goals. This role involves identifying AI use cases for efficiency, cost savings, and risk reduction, and collaborating across the program for consistent AI technology application. The architect will design and develop AI solutions using various techniques like machine learning, deep learning, NLP, and computer vision. A key aspect of the role is staying current with AI laws, policies, and frameworks, and using strong communication skills to articulate clear AI policies for ethical and secure AI practices. The position also requires leading and developing AI talent, identifying skill gaps, and upskilling program resources. The AI Architect will serve as the Subject Matter Expert (SME), providing knowledge sharing and mentoring to junior team members. Additionally, the role involves supporting R&D efforts, evaluating AI technologies, identifying business problems addressable by AI, and generating analysis to guide program direction and decision-making.

Requirements

Bachelor's degree in computer science, engineering, IT, related field or 10+ years of professional experience including at minimum 5+ years of experience in AI development, AI engineering, and AI architecture.
Deep understanding of AI principles, architectures, technologies, and governing security policies.
Must also be able to incorporate government security considerations in the design and development of AI-based solutions.
Ability to produce architecture and designs that implement scalability, performance, and cost-effective solutions.
Experience with machine learning, deep learning, natural language processing, and generative AI.
Sufficient programming skills in languages such as Python, Java, or C++ to demonstrate functionality and kickstart technical efforts.
Experience with self-hosted and cloud-based AI platforms such as AWS, Azure, or Google Cloud.
AWS cloud experience (GovCloud preferred), deploying computer, storage, and other native service offerings.
Experience with AI tools, technologies, and frameworks like Sagemaker, Pytorch, TensorFlow, Glue, Databricks, Elasticsearch, Azure AI, Pandas, NumPy, Jupyter Notebook.
Must be able to articulate proper uses, pros, cons, and lessons learned.
Strong communication and collaboration skills with technical and non-technical audiences to share ideas, program vision, and provide proper operational guidance.
Ability to work in a fast-paced environment with multiple priorities and deadlines.

Nice To Haves

4+ years managing, designing, building, and implementing enterprise technology solutions
4+ years incorporating security best practices for system integration and design, such as NIST Risk Management Framework (RMF)
4+ years delivering technical solutions for government customers on programs of at least $50M in total contract value
3+ years translating requirements into high level system designs
3+ years designing and implementing data management technologies
3+ years integrating systems, services, and/or components through standard or custom APIs
3+ years producing technical documentation to communicate system designs and technological analysis to both technical and non-technical audiences
Familiarity with Government Cyber Mission Space and legal constraints applicable to civilian Government Agencies (FISMA, FIPS, SecOps, etc.)
Experience with DevSecOps
Experience with Elastic Cloud Enterprise and other Elastic products
Experience in assessment, evaluation, and documentation of client environment, infrastructure, process, and operations.
Experience in data modeling, visualization, metric dashboards, and other reporting systems
Understanding of DHS CDM Program and understanding of cybersecurity requirements and mandates

Responsibilities

Define an AI strategy for the program, including appropriate AI architectures, principles, and technologies.
Develop program roadmaps that align with business goals and objectives.
Identify use cases where the use of AI results in efficiencies in processing, cost savings, and risk reduction.
Collaborate with the program at large to ensure consistent and proper use of AI technologies.
Develop and implement AI architectures that meet business requirements, using techniques such as machine learning, deep learning, natural language processing, and computer vision.
Design and develop AI-based solutions.
Stay up to date on modern AI-related laws, policies, and frameworks across commercial and government use.
Leverage strong oral and written communication skills to help craft and articulate clear AI policies, ensuring the ethical and secure practice of AI across various systems.
Identify major skillsets and roles needed to shape functional development of AI solutions across the program.
Develop AI resources from recruitment through career advancement to ensure the program limits skill gaps and can deliver AI-based solutions where appropriate.
As the program SME; provide knowledge sharing, educate, and generally upskill program resources to become familiar and comfortable with using AI to increase efficiencies in solving technical problems.
Mentor junior team members and provide guidance on AI principles, architectures, and technologies.
Support the evaluation, analysis, and R&D efforts associated with the integration of AI technologies through collaboration, guidance, and leadership.
Identify business problems, opportunities, and challenges that can be addressed with AI solutions.
Generate robust, consistent, and justifiable analysis outputs to help shape program direction and guide informed decision making.