Design, build, and optimize AI Agents using advanced methods (e.g., Naïve Bayes, Random Forests)
Explain AI concepts to both technical and non-technical audiences; facilitate training and pilot projects
Work across multi-cloud and on-premises environments, selecting appropriate cloud-native resources (e.g., AWS Bedrock, GCP Vertex AI, Docker, Kubernetes, MongoDB, BigQuery) to support AI initiatives
Assess and recommend AI technologies and techniques (e.g., GPT-4.0, Anthropic Claude, RAG, Neo4j, GraphRAG, multimodal AI, IBM Bee-Hive) for various business needs
Serve as an AI advocate, coaching and empowering teams to develop and deploy AI Agents
Apply best practices in AI governance, security, and compliance (e.g., NIST, OWASP, ATLAS-MITRE, GDPR)
Build AI Agents end-to-end using tools such as VS Code, Python, JavaScript, React.js, Node.js, pyspark, scikit-learn, Jupyter, SQL
Develop, train, and fine-tune machine learning models and large language models (LLMs)
Requirements
Bachelor’s degree in AI/ML Engineering, Computer Science, Data Science, or a related field (or equivalent experience)
1+ years experience creating end-to-end agentic workflows
Ability to obtain a U.S. 6C Security Clearance
Benefits
medical
dental
vision
HSA and FSA
generous earned time off
401K/student loan repayment
life insurance & AD&D insurance
employee assistance program
employee stock purchase program
tuition reimbursement
performance-based incentive pay
short- and long-term disability
robust wellness program
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AI AgentsNaïve BayesRandom Forestsmachine learning modelslarge language modelsend-to-end workflowsPythonJavaScriptSQLpyspark