Staff AI Full-Stack Engineer

Kohl's

. Lead development of robust, observable, and measurable applications using extreme programming practices and a user-centric approach .

Posted 10/3/2026full-timeMenomonee Falls • Wisconsin • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and scaling production applications using foundation models and agentic workflows, with a strong focus on application design patterns and performance optimization. Proven ability to lead teams, mentor junior members, and implement extreme programming practices to drive business outcomes.

Highest-signal resume keywords

Extreme Programming PracticesAI Application IntegrationApplication Design PatternsCloud Platforms (GCP, AWS, Azure)Performance Tuning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Application Lifecycle ManagementModular Backend Services DevelopmentAPI IntegrationStreaming Simulation FrontendsDistributed TracingContainerized MicroservicesTesting StrategiesEvent-Driven ArchitectureDatabase SchemasAI Application Quality Optimization

Soft Skills

Critical ThinkingMentoringCollaborationFeedback ModelingManaging Competing Priorities

Tools & Technologies

MCP GatewaysSecurity ProxiesIntegration SDKsTelemetry ToolsData Science Collaboration

Certifications & Qualifications

Bachelor's Degree in MIS, Computer Science or Related Field

Industry Keywords

Foundation ModelsRAG ArchitecturesAgentic WorkflowsLean ExperimentationHuman-in-the-Loop Workflows

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformMicroservices

About the role

Key responsibilities & impact

Lead development of robust, observable, and measurable applications using extreme programming practices and a user-centric approach
Navigate the entire application lifecycle with designers, product managers, and engineers
Leverage critical thinking, lead lean experimentation, and use data and industry best practices to drive business outcomes
Establish and lead product engineering and software standards
Mentor junior team members through pairing sessions, one-on-ones, and ad hoc guidance
Model partnership, collaboration, technical initiatives, and regular feedback
Champion and customize extreme programming practices
Design and build modular, headless AI backend services, advanced RAG architectures, and multi-agent orchestration workflows
Construct enterprise-grade MCP gateways, API integration/mediation layers, rate limiters, and security proxies
Develop streaming simulation frontends to validate agent behaviors, prompt strategies, and human-in-the-loop workflows
Collaborate with Applied/Data Science and Machine Learning specialists to fine-tune SLMs, perform AWQ/GPTQ quantization, and optimize GPU memory for inference
Instrument distributed tracing, token utilization logging, and inference latency telemetry
Package reusable code libraries, containerized microservices, and integration SDKs
Architect resilient Compound AI Systems routing between deterministic APIs, specialized SLMs, and frontier LLMs

Requirements

What you’ll need

6+ years of demonstrated experience building and scaling production applications using foundation models, RAG, or agentic workflows
6+ years of experience integrating AI applications securely with enterprise data, APIs, and identity/access controls
4+ years of experience evaluating and optimizing AI application quality, latency, reliability, and cost
6+ years of experience in software development
Proven ability to manage multiple competing priorities
Advanced knowledge of application design patterns, event-driven architecture, database schemas, and testing strategies
Experience with large-scale application troubleshooting and performance tuning
Demonstrated experience working with major cloud platforms (GCP, AWS, or Azure)
Knowledge and experience with continuous integration, continuous deployment, and test-driven development
Bachelor's Degree or equivalent in MIS, Computer Science or related field (preferred)