AI/ML Engineer/Architect

Position: AI/ML Engineer Location: California, Washington, Texas/Ohio/New Jersey/New York, Florida, PA, Georgia Terms: Long Term Contract/Fulltime • The Agentic AI Engineer will collaborate with data Scientists to build and deploy AI agents to both automate and optimize labor-intensive workflows. • The tasks of the Agentic AI Engineer will include writing software code to support AI agent communication, connecting models and agents to external/internal services via API calls, • support testing and debugging tasks, deployment into target environments, setting up monitoring, and ensuring reliable execution of agentic AI systems. • They will utilize a combination of open source models, agentic tools, and large proprietary commercial models. • They will be securing agentic workflows and to evaluating the results for accuracy, performance, and impact. • They will be expected to ensure AI systems adhere to ethical guidelines, transparency, and fairness principles. • They should be a self-starter while also working well within the team, collaborating and sharing discoveries and seeking feedback. • They should expect they may conduct research, develop prototypes, evaluate and document results. Skills: • 3+ years of experience building production-level AI or ML systems, including LLMs, agents, or complex automation frameworks • 3+ years of experience with Python and Python tools, including Pandas or NumPy • Experience with Large Language Models ( LLMs), Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL) • Good understanding and experience working with Natural Language Processing (NLP) • Experience with tools and AI agent frameworks such as TensorFlow, PyTorch, LangGraph, or LangChain • Experience in resolving workflow problems through automation optimization • Experience in connecting Agents to APIs, Cloud platforms, or databases • Ability to work with automated testing tools to perform testing and maintenance • Experience with Software Development Lifecycle (SDLC), such as DevSecOps • Experience with Cloud Service Providers such as Amazon Web Services (AWS) • Experience with developing REST services with Java and Spring Boot • Experience with the administration of continuous integration and continuous deployment ( CI / CD ) pipelines using Kubernetes, Docker, or Jenkins • Preferred experience working with GitHub and other collaborative development platforms.