Senior Generative AI Engineer

Role Overview

• Design and deploy production-grade Agentic AI systems where LLMs serve as operational components to reason, explain, and make decisions within live workflows
• Architect intelligent pipelines combining classical tools (OCR, fuzzy matching, structured query) with LLM-based validation, confidence scoring, fallback logic, and automated logging for auditability and continuous improvement
• Translate ambiguous mission requirements into well-scoped AI system designs; apply prompt and context engineering, RAG, semantic search, and fine-tuning as appropriate; leverage AWS services including Bedrock, Textract, Lambda, and Step Functions
• Use generative AI tooling to accelerate the full development lifecycle: requirements analysis, code generation, test coverage, documentation, and deployment scaffolding
• Document and quality-assure all project work prior to client delivery; attend meetings with agency staff, vendors, and external stakeholders as needed
• Lead or contribute to business development, internal tool-building, mentorship, or publication to strengthen Peregrine's AI capabilities and market position

Requirements

• AWS Certification required: Certified AI Practitioner, or relevant AWS Associate, Specialist, or Professional-level certification
• Hands-on proficiency with AWS tools such as Amazon Bedrock, Textract, Step Functions, Lambda, Glue, CloudFormation, CDK, Cognito and related AWS services
• Python fluency including LangChain and AWS Strands; experience with vector databases and embedding workflows
• Experience with Model Context Protocol (MCP) to connect LLMs to external tools, APIs, and data sources; ability to design and implement MCP servers and clients in production architectures
• Advanced SQL, cloud-native data pipeline management, and ETL workflows
• Expert knowledge of LLM behavior, confidence calibration, evaluation, and responsible AI principles. Knowledge includes explainability, auditability, and governance in regulated environments
• Experience with DevSecOps and MLOps: GitHub, CloudFormation, and related tools for version control, CI/CD, pipeline deployments, system and model monitoring, and drift detection
• Domain knowledge of federal data environments, government IT modernization, or public sector AI adoption
• Excellent written and oral communication skills; proven collaborator in professional or academic settings
• Bachelor’s required, advanced degree preferred; Computer Science, Data Science, AI, Applied Mathematics, Statistics, or related quantitative field strongly preferred
• 8+ years in software development, ML engineering, or data science; background in computer science or related technical and/or quantitative fields
• Multi-modal AI experience (vision, document understanding, structured extraction)
• Prior consulting, or client-services experience strongly preferred
• Open-source contributions or published GenAI research preferred
• Familiarity with OMB AI guidance and the NIST AI Risk Management Framework preferred
• U.S. citizenship; ability to obtain a Public Trust suitability determination required

Tech Stack

• AWS
• Cloud
• ETL
• Python
• SQL

Benefits

• Full health coverage (medical, dental, and vision) with 100% of employee premiums covered
• Life and disability insurance, fully covered by the company
• 401(k) retirement plan with 100% match on contributions up to 4% of salary with immediate vesting
• Unlimited Paid Time Off (PTO) to encourage work-life balance
• Remote location but greater Washington, DC area preferred for hybrid engagement
• Sponsored AWS certification training