AI Engineer (Active IRS MBI clearance)

Mission Bridge Partners•D.C., DC

About The Position

We are seeking an experienced AI Engineer to support a mission-critical modernization initiative for the Internal Revenue Service (IRS). The program focuses on transforming legacy tax processing systems, improving taxpayer experiences, enhancing operational efficiency, and reducing reliance on outdated technologies. The AI Engineer will develop and deploy enterprise AI solutions, with particular expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and Python. The role combines technical AI expertise and cloud engineering, and includes leading initiatives from concept through production deployment. The engineer will collaborate with technical teams, program leadership, and federal stakeholders to deliver secure, scalable, and responsible AI solutions.

Requirements

Active IRS MBI clearance and current Government-Furnished Equipment (GFE) are 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 RAG architectures.
Advanced knowledge of prompt engineering, LLMs, and Generative AI application development.
Experience developing, evaluating, optimizing, and deploying machine learning models.
Understanding of cloud infrastructure, containerization, and modern software development practices.
Experience with Git, automated testing, CI/CD pipelines, and production application deployment.
Demonstrated success supporting complex AI/ML initiatives from design through implementation.
Strong technical leadership, project coordination, and Agile delivery experience.
Ability to translate complex technical concepts into actionable recommendations for federal stakeholders.

Nice To Haves

Experience supporting IRS modernization initiatives or other federal civilian technology programs.
Hands-on experience with AWS GovCloud and secure federal cloud environments.
Experience implementing enterprise Generative AI applications using Azure OpenAI Service.
Familiarity with vector databases, embeddings, semantic search, and LLM orchestration frameworks.
Experience with LangChain, LlamaIndex, Hugging Face, or similar AI development frameworks.
Knowledge of responsible AI frameworks, LLM evaluation methodologies, and AI security guardrails.
Experience with RLHF, model fine-tuning, and advanced NLP techniques.
Familiarity with Docker, Kubernetes, Terraform, and MLOps practices.
Experience integrating AI capabilities into existing enterprise applications and legacy systems.

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 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 using Azure OpenAI, AWS cloud services, and cloud-native architectures.
Develop scalable AI/ML pipelines for model training, evaluation, deployment, and monitoring.
Implement CI/CD pipelines, automated testing, experiment tracking, and version control using Git.
Use 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 use 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 technical and nontechnical stakeholders.
Support Agile development activities, technical documentation, and cross-functional knowledge sharing.