AI Architect

InterSources, Inc.

$120K — $160K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years' experience in cloud and distributed systems architecture centered on scalability and reliability
  • 7+ years designing enterprise AI/ML systems with recent hands-on experience in GenAI and multi-agent systems
  • Strong expertise with agentic frameworks and tools like MCP, LangChain, and OpenAI SDK
  • Proven experience in modern software development practices
  • Ability to create AI-driven prototypes and demos quickly
  • Experience in establishing enterprise architecture standards and reference architectures
  • Familiar with AIOps/MLOps stacks and security considerations for AI systems

Responsibilities

  • Define the architecture for Kroger's agent-based integrations and orchestration
  • Govern architecture standards ensuring consistency and reliability across platforms
  • Collaborate with engineering, product, and data science teams for safe agent development
  • Rapidly develop prototypes and proofs of concept for the agent ecosystem
  • Design and manage infrastructure for scoring and evaluation pipelines
  • Enhance observability and performance of multi-agent systems
  • Establish governance for security and compliance in enterprise AI systems

Benefits

  • Health, dental, and vision insurance
  • 401(k) retirement plan
  • Flexible work hours and remote work options
  • Generous paid time off and holidays
  • Continuous learning and professional development opportunities
Full Job Description
SUMMARY
The AI Enablement team at Kroger/84.51° is seeking an AI Architect - Agentic Platforms to define the architectural foundations that power Kroger's enterprise agent ecosystem. This role is responsible for designing and governing the architecture for agent-based integrations, agent registries, scoring/evals infrastructure, grounding patterns, and multi-agent orchestration platforms. The AI Architect provides deep technical leadership across engineering, product, data science, security, and cloud teams to ensure that agents are built safely, consistently, and with enterprise-grade reliability, performance, and observability. This role combines expertise in large-scale AI systems, distributed cloud architecture, and modern agentic frameworks.
  • 10+ years' experience in cloud and distributed systems architecture focused on scalability, reliability, observability, and performance.
  • 7+ years designing enterprise AI/ML systems; 1+ years hands-on with GenAI, agentic workflows, RAG, LLM-based integrations, or multi-agent systems.
  • Strong expertise with agentic frameworks and tooling (MCP, LangChain, LangGraph,LlamaIndex, autogen, crewai, Agent sdk,OpenAI SDK etc).
Hands-on experience in modern software development and engineering practices.
Proven experience integrating APIs and enterprise systems into agentic platforms and workflows.
Ability to rapidly build AI-driven prototypes, proofs of concept, and demo-ready product experiences.
  • Experience defining and governing enterprise architecture standards, patterns, and reference architectures.
  • Deep understanding of MCP servers, tool calling, registries, eval pipelines, agent observability, and multi-agent orchestration.
  • Hands-on experience with Azure and GCP, including Kubernetes, containerization, identity, networking, CI/CD, and API platforms.
  • Familiarity with AIOps/MLOps stacks (MLflow, model registries, vector DBs, semantic layers, feature stores, monitoring).
  • Strong knowledge of security, compliance, risk, and Responsible AI (RAI) considerations for enterprise agent systems.
  • Demonstrated ability to partner across engineering, data science, product, and security teams to deliver complex AI platform architectures.

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