Director Ai/Ml Engineering - Superagents (P4478)

Director AI/ML Engineer - SuperAgents (P4478)

84.51° | Cincinnati, OH • Chicago, IL

84.51° Overview

84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

Summary

We're looking for a Senior Staff AI Engineer to design, build, and scale Kroger's customer-facing AI shopping agents and internal agentic systems. In this role, you'll be hands-on-writing code, deploying solutions, and ensuring every interaction delivers a seamless experience for millions of customers. This is a highly technical individual contributor position focused on execution and innovation.

You'll collaborate across functions-partnering with platform teams to scale infrastructure, integrating with domain services, and working closely with business leaders to align capabilities with measurable outcomes. Your work will power agents that understand customer intent, search products, manage carts, personalize recommendations, and complete transactions. Other agentic experiences could reach various internal populations across the Kroger Co.

This is a high-autonomy, high-accountability role.

What you'll do:

• Architect and implement conversational agents that serve millions of customers.
• Own the full technology stack: LLM/SLM selection, agent orchestration, RAG pipelines, production deployment, and ongoing operations.
• Lead and mentor a team of AI Engineers responsible for end-to-end agentic commerce delivery.
• Drive system design and roll up your sleeves to solve complex technical challenges.

What we're looking for:

• Proven experience of building and supporting AI Products to production at scale.
• Ability to innovate, troubleshoot, and continuously improve without waiting for someone else to figure it out.
• Translate business requirements into technical specifications and optimize for business value.

Responsibilities

Build and Ship AI Shopping Agents

• Design, develop, and deploy customer-facing conversational shopping agents for web, mobile, and voice while optimizing for cost, AI Safety and Business outcomes.
• Architect multi-step agent workflows: product discovery, personalized recommendations, cart management, order tracking, checkout assistance
• Build and optimize agentic systems grounded in Kroger's product catalog, inventory, pricing, and customer data.
• Implement agent orchestration using Google ADK, Open AI Agents SDK or equivalent frameworks
• Fine-tune and prompt-engineer LLMs for shopping-specific tasks
• Integrate agents with Kroger's e-commerce platform, inventory systems, and fulfillment APIs

Own Production Operations (AgentOps)

• Deploy and operate agents at scale-millions of customers, sub-second latency, 99.9%+ uptime
• Build observability infrastructure: tracing, logging, evaluation pipelines, cost monitoring
• Implement safety guardrails: toxicity detection, hallucination mitigation, PII protection
• Design and run continuous evaluation: LLM-as-judge, human feedback loops, A/B testing
• Own incident response. Debug production issues. Ship fixes fast.

Drive Technical Direction

• Set technical standards for agent development across teams
• Evaluate and select LLM providers, vector databases, and orchestration tools
• Define agent architecture patterns that scale across use cases
• Mentor senior engineers on LLM and agent best practices
• Translate Kroger's business objectives into agent capabilities

Qualifications

Required

• 7+ years Software engineering or ML engineering experience
• 5+ years building and deploying ML/AI systems in production
• 2+ years hands-on experience with LLMs in production (not just prototypes)
• 2+ years building and operating AI agents that serve real users at scale
• Expert Python. You write production code, not notebooks.
• Deep expertise in LLM fine-tuning, prompt engineering, and RAG architectures
• Hands-on experience with agent orchestration frameworks (Google ADK, LangGraph, Open AI Agents SDK, Semantic Kernel, or custom)
• Production experience with vector databases (Vertex AI, Azure Search or equivalent)
• Strong distributed systems fundamentals-you understand latency, throughput, reliability at scale
• Experience with cloud ML infrastructure (GCP Vertex AI, or Azure AI)
• Track record of owning systems end-to-end: design, build, deploy, operate, iterate

Technical Stack

• Languages: Python (primary), TypeScript
• LLM/Agent: Google ADK, OpenAI API or any agent framework including custom
• Observability: custom evaluation pipelines, Dynatrace, Vertex AI, Datadog etc.
• Infrastructure: GCP, Kubernetes, Vertex AI, Memory Systems for Agents
• Protocols: A2A, MCP, GRPC, WebSocket,
• Data: Big Query, SQL, GraphQL

Preferred

• Experience building customer-facing assistants or chatbots
• E-commerce or retail technology background , especially recommender systems and search
• Experience with streaming architectures and real-time systems with websockets,
• Familiarity with Google Vertex AI

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