Senior Manager, AI Engineer (AI)

Location: Atlanta, Georgia, United States. Onsite role with 0–25% travel. Relocation is not provided. Applicants must already be authorized to work full-time in the United States; visa sponsorship is not available.

Annual base pay: $152,000–$178,300 USD. Annual incentive reference value: 15%.

Company

Global beverage company advancing its digital transformation through data-driven products and enterprise technology.

What you will do

• Design, build, deploy, and operate domain-specific AI agents and GenAI solutions for enterprise digital products.
• Develop production-grade Python code, optimize inference pipelines, and maintain reliable, secure, observable AI systems.
• Deploy AI solutions on Azure and build MLOps pipelines for training, versioning, inference, monitoring, and CI/CD.
• Integrate AI capabilities into enterprise platforms, APIs, workflows, data systems, and user-facing products.
• Build evaluation frameworks, telemetry, tracing, regression tests, quality scoring, guardrails, and runtime safety controls.
• Design multi-agent systems, retrieval pipelines, digital twin capabilities, and LLMOps or AgentOps processes.

Requirements

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Software Engineering, or a related technical field.
• 3–5+ years of hands-on AI or ML engineering experience taking solutions from development to production.
• Strong Python skills and working knowledge of Java or C++.
• Experience with LLM-powered and agentic applications, frameworks such as LangChain, LangGraph, CrewAI, Semantic Kernel, MCP, or A2A, and production cloud deployment.
• Experience with vector databases, embeddings, RAG, GraphRAG, semantic search, APIs, MLOps, LLMOps, AgentOps, Docker, Kubernetes, CI/CD, and AI observability.
• Current full-time United States work authorization is required; employment visa sponsorship is not available.

Nice to have

• Azure experience is strongly preferred; AWS or GCP experience is also acceptable.
• Experience with responsible AI, runtime guardrails, explainability, data privacy, and secure agent execution.
• Experience supporting enterprise digital twins and complex multi-agent workflows.

Culture & Benefits

• Agile engineering environment with sprint planning, backlog refinement, code reviews, and cross-squad collaboration.
• Work alongside technical leads, software engineers, data engineers, product teams, and AI engineers.
• Focus on continuous learning, inclusive collaboration, experimentation, and engineering quality.
• Medical, financial, and other benefits are offered depending on the position.