LLM Engineer | Hybrid

Position: AI/ML Engineer Type: Full-Time Compensation: $150K – $400K/yr Location: Hybrid/Onsite Commitment: 10-40 hours/week Role Responsibilities • Design, implement, and optimize AI/ML models leveraging LLMs, RAG, and prompt engineering for production-grade applications. • Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain. • Integrate and deploy solutions in secure cloud environments including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock. • Build and maintain robust data pipelines, ETL processes, metadata catalogs, and ontologies to support high-quality AI training and inference. • Develop REST APIs and SDK integrations to enable seamless interaction between models and systems. • Collaborate with product, security, and engineering teams to ensure secure and scalable delivery aligned with DevOps and CI/CD best practices. • Document architectural decisions and communicate technical concepts clearly to technical and non-technical stakeholders. Requirements • Strong proficiency in Python for AI/ML development, including REST APIs and SDK integrations. • Hands-on experience deploying LLM and RAG systems in production environments. • Experience with multi-agent orchestration and frameworks such as LangGraph or LangChain. • Deep familiarity with cloud AI platforms including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, or AWS Bedrock. • Experience building data pipelines, ETL systems, metadata catalogs, and ontologies. • Strong understanding of secure coding practices and modern DevOps workflows including CI/CD pipelines. • Excellent written and verbal communication skills for cross-functional collaboration and documentation. Application Process • Upload resume • Interview (15 min) • Submit form