AI/ML Engineer - Remote
AI/ML Engineer Job Type: Full-Time Location: Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure, scalable AI solutions for mission-critical initiatives while contributing to proprietary AI infrastructure. You will work with LLMs, RAG, prompt engineering, multi-agent systems, and cloud AI platforms to develop production-grade machine learning applications.
Key Responsibilities
- Design, implement, and optimize AI/ML solutions using LLMs, RAG, and prompt engineering.
- Develop and orchestrate multi-agent systems using LangGraph and LangChain.
- Deploy AI solutions across secure cloud environments such as AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
- Build robust ETL and data pipelines, metadata catalogs, and ontologies for AI training and inference.
- Develop and maintain REST APIs and SDK integrations.
- Collaborate with product, security, and engineering teams to deliver secure, scalable solutions.
- Follow modern secure coding, DevOps, and CI/CD practices.
- Document technical decisions and communicate complex concepts effectively to technical and non-technical stakeholders.
Required Skills & Qualifications
- Strong Python proficiency for AI/ML development, including REST APIs and SDK integrations.
- Hands-on production experience with LLMs, RAG, and prompt engineering.
- Experience with multi-agent orchestration, tool use, LangGraph, and LangChain.
- Strong knowledge of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
- Experience building data pipelines, ETL processes, metadata catalogs, and ontologies.
- Strong understanding of secure coding and CI/CD practices.
- Excellent written and verbal communication skills.
Preferred Qualifications
- Experience with enterprise AI platforms such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
- Knowledge of MCP, metadata catalog platforms, and advanced API development.
- Experience working in government, regulated, or security-sensitive cloud environments.
- Familiarity with relevant compliance and security standards.