AI/ML Research Engineer – Full-Stack Experience
Location: Remote
Must have ability to obtain secret clearance - Must be US Citizen
Job Summary
We are seeking an experienced AI/ML Research Engineer with full-stack development expertise to help design, build, and deploy agentic AI applications at scale. The ideal candidate will have deep experience with LLMs, prompt engineering, NLP, and enterprise-scale data environments. You will work closely with cross-functional teams to develop AI assistant products, implement agentic workflows, and optimize AI pipelines for real-world applications.
Job Responsibilities
- Design, develop, and deploy agentic AI applications and AI assistant-style products.
- Implement LLM-based solutions with effective prompt engineering and fine-tuning strategies.
- Build scalable NLP pipelines and work with enterprise data systems such as SAP HANA, DB2, and SQL Server.
- Integrate AI solutions with enterprise-scale platforms, including prior experience with Lockheed Martin or similar environments.
- Collaborate with data scientists, engineers, and stakeholders to define architecture, workflow, and system requirements.
- Apply best practices in ontology frameworks, knowledge management, and AI model governance.
- Utilize cloud AI/ML platforms (AWS ML, Azure AI) to deploy and manage models at scale.
- Solve complex problems using critical thinking, predictive modeling, and state-of-the-art AI/ML technologies.
Job Requirements
- Bachelor’s degree in Computer Science, Data Science, Systems Engineering, or a related field, or equivalent experience.
- Strong proficiency in Python and hands-on experience with LLM prompt engineering.
- Experience with agentic AI frameworks and building agentic AI workflows in production systems.
- Deep understanding of NLP techniques and deploying scalable AI models.
- Solid SQL expertise and experience with enterprise data platforms (SAP HANA, DB2, SQL Server).
- Relevant cloud AI/ML certifications (e.g., Azure AI Engineer, AWS ML).
- Ability to differentiate between data models (e.g., Meta vs. OpenAI) based on project needs.
- Strong problem-solving, critical thinking, and collaborative skills.
Desired Skills
- Experience with Node.js and building web-based AI applications.
- Knowledge of Model Context Protocol (MCP).
- Predictive modeling experience.
- Comfort working in fast-paced, rapidly evolving environments.
Screening Focus Areas
Candidates should be prepared to discuss:
- Experience designing and using ontology frameworks, including governance best practices.
- Agentic AI workflows and frameworks, and their application in production systems.
- Prompt engineering versus model fine-tuning strategies for LLMs.
- Approaches to chunking PDFs, handling tables, and designing RAG systems.
- Vector database concepts, embedding model selection, and limitations of embedding models.
