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Principal AI Engineer (Agentic AI)
Jobtailor
1 hour ago
Full-time
On-site
Vienna, Virginia, United States
Develop and implement AI-driven solutions that enhance and scale AI adoption across Navy Federal Credit Union.
Lead the design and implementation of cutting-edge AI systems using large language models to solve complex business problems.
Collaborate with ETS and Business partners to build and drive AI solutions.
Provide delivery and ongoing support for data science, advanced analytics, and augmented intelligence technologies.
Exhibit excellent problem-solving skills and demonstrate strong leadership qualities with a proven track record of delivering measurable outcomes.
Requirements
Bachelor's Degree in Computer Science, Statistics, Engineering or related field, or the equivalent combination of education, training and experience. 7-10 years of experience in AI or similar. Experience with modern Generative AI and agentic patterns (e.g., LLM workflows, orchestration frameworks, RAG, grounding, evaluation, safety controls). Experience establishing AI standards, best practices, and scalable enablement mechanisms (reference architectures, reusable components). Proven track record of driving and coordinating use of GenAI Code Assistants (GitHub Copilot, etc.) to drive Developer Productivity initiatives across the organization with clear value metrics. Hands-on experience building production grade AI agents using industry leading platforms (Azure AI Foundry, etc.) and related technologies such as MCP or A2A. Experience with data platforms (Databricks, etc.) and organizing, cataloging and chunking of unstructured data for scalable Generative-AI solutions and robust knowledge management. Experience with vector stores and graph databases for managing complex relationships to use in AI applications such as recommendation systems. Robust experience in Azure AI/Data solutions and a deep understanding of the evolving AI landscape, with proven track record in API integrations for accessing LLMs. Demonstrated experience conducting threat modeling and implementing security controls for AI systems, including prompt-injection defenses, data-loss prevention, agent authorization, secure tool execution, secrets management, and adversarial testing. Experience operationalizing Responsible AI and model-risk requirements through technical controls, evaluation criteria, documentation, human-in-the-loop patterns, traceability, and auditable evidence. Advanced software engineering skills in Python and API/service development, with experience designing distributed, resilient, containerized systems and implementing automated testing Experience with Agile/SAFe delivery and CI/CD practices for AI solutions. Significant experience working with structured and unstructured data. Significant experience in developing sophisticated algorithms to automate processes and tasks. Advanced knowledge of current AI technologies and concepts.
Core Competencies Demonstrates expertise in developing and implementing AI-driven solutions, with a strong focus on Generative AI, data science, and advanced analytics. Proven ability to lead teams, establish AI standards, and operationalize Responsible AI practices while delivering measurable outcomes. #J-18808-Ljbffr
Requirements
Bachelor's Degree in Computer Science, Statistics, Engineering or related field, or the equivalent combination of education, training and experience. 7-10 years of experience in AI or similar. Experience with modern Generative AI and agentic patterns (e.g., LLM workflows, orchestration frameworks, RAG, grounding, evaluation, safety controls). Experience establishing AI standards, best practices, and scalable enablement mechanisms (reference architectures, reusable components). Proven track record of driving and coordinating use of GenAI Code Assistants (GitHub Copilot, etc.) to drive Developer Productivity initiatives across the organization with clear value metrics. Hands-on experience building production grade AI agents using industry leading platforms (Azure AI Foundry, etc.) and related technologies such as MCP or A2A. Experience with data platforms (Databricks, etc.) and organizing, cataloging and chunking of unstructured data for scalable Generative-AI solutions and robust knowledge management. Experience with vector stores and graph databases for managing complex relationships to use in AI applications such as recommendation systems. Robust experience in Azure AI/Data solutions and a deep understanding of the evolving AI landscape, with proven track record in API integrations for accessing LLMs. Demonstrated experience conducting threat modeling and implementing security controls for AI systems, including prompt-injection defenses, data-loss prevention, agent authorization, secure tool execution, secrets management, and adversarial testing. Experience operationalizing Responsible AI and model-risk requirements through technical controls, evaluation criteria, documentation, human-in-the-loop patterns, traceability, and auditable evidence. Advanced software engineering skills in Python and API/service development, with experience designing distributed, resilient, containerized systems and implementing automated testing Experience with Agile/SAFe delivery and CI/CD practices for AI solutions. Significant experience working with structured and unstructured data. Significant experience in developing sophisticated algorithms to automate processes and tasks. Advanced knowledge of current AI technologies and concepts.
Core Competencies Demonstrates expertise in developing and implementing AI-driven solutions, with a strong focus on Generative AI, data science, and advanced analytics. Proven ability to lead teams, establish AI standards, and operationalize Responsible AI practices while delivering measurable outcomes. #J-18808-Ljbffr