Position Overview
We are seeking an experienced AI Engineer to support a mission-critical modernization initiative for the Internal Revenue Service (IRS). This program focuses on transforming legacy tax processing systems, improving taxpayer experiences, enhancing operational efficiency, and reducing reliance on outdated technologies.
The ideal candidate will bring strong hands-on experience developing and deploying enterprise AI solutions, with particular expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and Python development.
This position requires a combination of deep technical expertise, cloud engineering capabilities, and the ability to lead AI initiatives from concept through production deployment. The AI Engineer will collaborate with technical teams, program leadership, and federal stakeholders to deliver secure, scalable, and responsible AI solutions.
Key Responsibilities
Design, develop, and deploy enterprise-grade AI and Generative AI applications using Python, Azure OpenAI, AWS, and open-source frameworks.
Architect and implement Retrieval-Augmented Generation (RAG) solutions to improve the accuracy, relevance, and reliability of LLM-generated responses.
Develop, test, and optimize advanced prompt engineering strategies for complex business and technical use cases.
Evaluate, fine-tune, and optimize machine learning and language models to meet performance, accuracy, and operational requirements.
Implement responsible AI practices, including model evaluation, guardrails, security controls, and risk mitigation.
Explore and implement advanced AI techniques, including reinforcement learning from human feedback (RLHF), natural language processing (NLP), and model optimization.
Build and deploy AI applications leveraging Azure OpenAI, AWS cloud services, and cloud-native architectures.
Develop scalable AI/ML pipelines supporting model training, evaluation, deployment, and monitoring.
Implement CI/CD pipelines, automated testing, experiment tracking, and version control using Git.
Leverage Docker, Kubernetes, and infrastructure-as-code practices to support reliable and maintainable AI environments.
Ensure AI solutions align with federal security, compliance, and operational requirements.
Lead the technical implementation and delivery of AI initiatives across multiple projects and stakeholder groups.
Collaborate with software engineers, cloud architects, data scientists, and program leadership to integrate AI capabilities into enterprise applications.
Identify opportunities to leverage AI and automation to improve business processes and operational efficiency.
Establish AI engineering standards, development best practices, and reusable solution architectures.
Conduct technical reviews, troubleshoot complex challenges, and provide guidance on AI solution design.
Communicate technical concepts, project progress, and recommendations to both technical and nontechnical stakeholders.
Support Agile development activities, technical documentation, and cross-functional knowledge sharing.
Required Qualifications
Active IRS MBI clearance and current Government-Furnished Equipment (GFE) required.
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical discipline.
7+ years of relevant experience in software engineering, AI/ML development, cloud engineering, or related technical disciplines.
Strong hands-on experience developing AI applications using Python.
Demonstrated experience working with Azure OpenAI and AWS cloud services.
Proven expertise designing and implementing Retrieval-Augmented Generation (RAG) architectures.
Advanced knowledge of prompt engineering, Large Language Models (LLMs), and Generative AI application development.
Experience developing, evaluating, optimizing, and deploying machine learning models.
Understanding of cloud infrastructure, containerization, and modern software development…