Software AI Engineer

Key Responsibilities

• Design, build, and deploy advanced AI/ML solutions for government clients, ensuring robust and secure implementation at scale.
• Collaborate with internal and external teams to architect and enhance AI-driven platforms, focusing on RAG, LLM orchestration, and multi-agent workflows.
• Develop and maintain APIs, SDK integrations, and scalable pipelines, utilizing Python and RESTful best practices.
• Leverage cloud platforms such as AWS GovCloud, Vertex AI, and AWS Bedrock to deliver secure, enterprise-grade solutions.
• Implement data ontologies, metadata catalogs, and ETL pipelines to support advanced AI and analytics use cases.
• Apply best practices in prompt engineering, LangGraph/LangChain, and tool integration for agentic AI systems.
• Ensure clear, concise, and effective written and verbal communication across all collaborative efforts.

Required Skills and Qualifications

• Proven experience with large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI techniques.
• Expertise in Python development, REST API design, and secure coding principles.
• Hands-on knowledge of AWS, and familiarity with other government cloud offerings (e.g., Google GovCloud, Azure IL).
• Demonstrated ability to work with AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, and Grok Enterprise.
• Strong background in building and maintaining robust data pipelines and ontologies.
• Proficiency in CI/CD practices for deploying production AI/ML systems.
• Exceptional written and verbal communication skills, with the ability to articulate complex concepts to both technical and non-technical stakeholders.

Preferred Qualifications

• Experience with advanced agent orchestration frameworks such as LangGraph and LangChain.
• Background in secure, scalable government or enterprise deployments of AI/ML solutions.
• Knowledge of metadata catalogs, MCP, and multi-cloud environments.