Atlanta, GA (EST time zone preferred)
Employment Type:
Contract
REMOTE
GC/USC
7+ years in AI/ML and data engineering, expertise in Agentic AI frameworks (LangGraph, CrewAI, Semantic Kernel), Python, generative AI, RAG/NLP, Vector DBs, Knowledge Graphs, GCP (Vertex AI, BigQuery, Cloud Functions, Pub/Sub), and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Role Summary:
We are seeking a
Lead AI Engineer
to drive the design and development of a next-generation Agentic AI platform. This high-impact role will shape the technical strategy and infrastructure behind autonomous systems, including LLM-based pipelines, agent orchestration, and vector-based memory. The ideal candidate combines strategic vision with hands-on expertise, delivering scalable, intelligent AI-driven solutions.
Key Responsibilities:
Lead the design, architecture, and development of scalable Agentic AI systems.
Build and optimize LLM pipelines, agent orchestration frameworks, and memory systems using vector databases.
Implement core infrastructure on GCP, leveraging services such as Vertex AI, BigQuery, Cloud Functions, and Pub/Sub.
Develop, fine-tune, and evaluate ML models and orchestration workflows.
Drive technical strategy, tooling, and infrastructure decisions across AI initiatives.
Conduct model evaluation, A/B testing, and performance benchmarking.
Collaborate effectively with cross-functional Agile teams to deliver high-impact solutions.
Stay up-to-date with emerging research and technologies in agentic and generative AI.
Key Requirements:
7+ years of experience in AI/ML, data engineering, and large-scale program delivery.
Deep expertise in Agentic AI architectures and frameworks (e.g., LangGraph, CrewAI, Semantic Kernel).
Strong proficiency in Python for scalable application development and performance optimization.
Hands-on experience with generative AI, NLP, and RAG (Retrieval-Augmented Generation) architectures.
Proven experience designing and implementing IR/RAG systems with Vector DBs and Knowledge Graphs.
Familiarity with cloud-native development and GCP services.
Experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Excellent communication skills and ability to adapt in fast-paced, innovative environments.