Senior AI/ML Engineer
$135,000–$216,000 year
RemoteUnited States or US
Job Summary
Lead the design and implementation of generative AI solutions, including rapid prototypes and production pilots. Architect and deploy agent-based LLM workflows with structured outputs, multi-agent orchestration, tool integration, and validation mechanisms. Perform end-to-end data engineering and analysis using Python, R, and SQL; develop dashboards and visualizations to communicate insights. Apply modern software engineering practices (Git, CI/CD, DevSecOps) to transition AI models from development to secure production environments. Translate mission and business requirements into scalable technical designs; effectively communicate AI concepts to non-technical stakeholders. Integrate AI-driven automation with enterprise systems, APIs, and databases. Develop reusable frameworks, best practices, and toolkits to enable enterprise-wide AI adoption. Ensure compliance with data security, privacy, and ethical AI standards; implement guardrails, monitoring, and responsible AI controls. Mentor engineers and data scientists; contribute to documentation, knowledge sharing, and AI governance practices.
Required Qualifications
- Bachelor's degree with 12+ years of experience, Master's with 10+ years, or PhD with 7+ years in Computer Science, Engineering, Physics, Mathematics, or related STEM discipline
- US Citizenship
- ability to obtain and maintain a Public Trust clearance
- Demonstrated experience building, deploying, and optimizing AI/ML solutions in production environments
- Hands-on experience designing agentic AI architectures and autonomous workflows
- Strong programming proficiency in Python
- experience with C/C++ or JavaScript
- Experience integrating and consuming APIs from state-of-the-art LLM providers
- Demonstrated expertise in prompt engineering, Retrieval-Augmented Generation (RAG), model fine-tuning, and evaluation techniques
- Familiarity with modern development environments and tool chains (e.g., Visual Studio Code, Git-based workflows)
Desired Qualifications
- Experience with ML frameworks such as TensorFlow or PyTorch
- Experience with advanced data science techniques using R
- Familiarity with agent development frameworks and emerging interoperability standards such as Anthropic's Model Context Protocol (MCP)
- Experience leveraging AI coding assistants (e.g., GitHub Copilot, Microsoft Copilot, Claude Code capabilities) to accelerate development workflows
- Experience working with platforms such as Azure OpenAI, GPT models, Claude, or Gemini
- Relevant certifications (AWS Machine Learning Specialty, Azure AI Engineer Associate, Google Professional ML Engineer, DeepLearning.AI certifications)
Additional Requirements
- US Citizenship required; must have the ability to obtain and maintain a Public Trust clearance.
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