Here is OUR CLIENT REQUIREMENT which can be filled immediately.
Position: AI Engineer
Location: Alpharetta, GA
Duration: Contract W2
Bachelor's degree or equivalent experience
6+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
2+ years in a dedicated AI/ML role, with hands-on experience in model integration, MLOps, and applying AI to solve business problems.
1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
2+ years of in-depth experience with Google Cloud Platform (Google Cloud Platform), specifically its AI/ML services (Vertex AI, etc.).
3+ years of proven experience leveraging Kubernetes workloads.
Proficiency in Python, JavaScript/TypeScript and/or Java and working knowledge of a modern front-end framework (Angular, React, or Vue) to collaborate effectively with UI teams.
Hands-on experience with LLM observability tools like Langfuse for monitoring and debugging agentic workflows
Cloud-Native Proficiency:
Cloud Platforms: Extensive hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).
Containerization: Mastery of Docker for containerizing applications and Kubernetes for orchestration.
Infrastructure as Code (IaC): Proficiency with tools like Terraform or CloudFormation to manage infrastructure programmatically.
CI/CD Tools: Experience with CI/CD tools such as Github Actions, Argo CD, Jenkins
Database Knowledge: Strong experience with both SQL (e.g., Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB and Firestore) databases.
What could set you apart
Strong expertise in Generative AI (GenAI), including hands-on experience with models like Gemini, ChatGPT, Claude, or Llama.
You are adept at leveraging modern development tools, including AI-powered code assistants (like GitHub Copilot), to accelerate the development lifecycle and rapidly ship high-quality features
Experience creating and deploying AI agents to production environments.
You have a history of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.
You are passionate about the potential of AI, but you are grounded in the practical realities of building and shipping reliable, production-ready software.
