REI Systems is seeking a Principal AI Engineer to provide strategic and hands-on technical leadership in AI for Federal clients. This role integrates AI across cloud modernization and digital transformation initiatives, guiding agencies to adopt secure, scalable, and responsible AI capabilities that align with mission needs and compliance.
What You'll Do
- Architect and design scalable AI/ML solutions using cloud platforms such as AWS, Azure, and Google Cloud Vertex AI.
- Develop AI-driven prototypes and PoCs, including GenAI/RAG and agentic workflow demonstrations.
- Define target architectures for LLMOps/MLOps, including model lifecycle management, evaluation, deployment patterns, and security controls.
- Build, train, deploy, and optimize machine learning models using PyTorch, Hugging Face, Scikit-learn, and LangChain/LangGraph.
- Implement agentic AI patterns such as tool/function calling, planner-executor flows, structured output, and human-in-the-loop workflows.
- Design and optimize data pipelines for AI workflows, leveraging platforms like Databricks and Snowflake.
- Implement modern unstructured data pipelines for document ingestion, embedding generation, and vector search.
- Deploy AI models in cloud environments, ensuring scalability and performance using containers/Kubernetes, CI/CD, and infrastructure-as-code.
- Monitor and maintain deployed models with observability, drift detection, and cost controls.
- Partner with internal account teams to support pre-sales and sales activities, presenting AI solutions to Federal clients.
- Provide technical leadership and mentorship to junior team members on AI/ML methodologies and best practices.
- Advise on integrating low-code platforms like Salesforce and Appian into AI/ML solutions.
- Stay current on advancements in AI technologies, including agent frameworks and responsible AI governance.
What We're Looking For
- 8+ years of total experience with at least 4+ years in AI/ML solution design and implementation.
- Proven track record with cloud-based AI/ML platforms (AWS, Azure, GCP), including production deployments.
- Proficiency in Python and experience with ML frameworks such as PyTorch, Scikit-learn, Hugging Face, and LangChain/LangGraph.
- Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques, including LLM/agent evaluation.
- Experience with cloud AI/ML services such as AWS SageMaker, AWS Bedrock, Azure ML / Azure AI Studio, or Vertex AI.
- Familiarity with big data platforms like Snowflake and Databricks.
- Experience with RAG architectures, Knowledge Graphs, Vector Search, and agent orchestration/tooling.
- Strong problem-solving abilities and critical thinking skills.
- Excellent communication and interpersonal skills, with the ability to articulate technical concepts to non-technical audiences.
- Adaptability and eagerness to stay updated with evolving AI/ML technologies.
- Ability to obtain and maintain relevant security clearances.
Nice to Have
- Demonstrated GenAI/LLM delivery experience.
- Experience with MLOps/LLMOps tooling (e.g., MLflow, model registries, CI/CD, monitoring/observability).
- Understanding of low-code platforms with AI capabilities, such as Salesforce and Appian.
- AI/ML certifications (e.g., AWS Machine Learning Specialty, AWS Generative AI, Azure AI Engineer).
- Experience working with Federal agencies or large-scale enterprises.
- Familiarity with ethical AI principles and responsible AI practices, including governance and model risk considerations.
Technical Stack
- Cloud Platforms: AWS, Azure, Google Cloud Vertex AI
- ML Frameworks: PyTorch, Hugging Face, Scikit-learn, LangChain/LangGraph
- Data Platforms: Databricks, Snowflake
- Cloud AI Services: AWS SageMaker, AWS Bedrock, Azure ML / Azure AI Studio, Vertex AI
- Low-Code Platforms: Salesforce, Appian
REI Systems is proud to be recognized as a Washington Post Top Workplace.
