Senior Engineer 2, AI Enablement (Hybrid - Seattle, WA)

Nordstrom•Seattle, WA

23h•$166,000 - $258,000•Hybrid

About The Position

As a Senior Engineer 2 on our AI Enablement team, you will be a lead technical contributor responsible for designing and delivering complex AI platform capabilities. You will ensure that all designs are clear and complete for successful execution while making technical decisions that balance short and long-term business objectives. This is an opportunity to drive the technical strategy of AI enablement at Nordstrom, acting as a subject matter expert and making transformative impact on how thousands of engineers leverage AI technology. A key dimension of this role is ownership of security and identity for AI systems – including how we authenticate, authorize, and protect AI services and the sensitive data they process. You will be expected to champion security-first engineering practices across the team and the broader organization. A day in the life... Technical Leadership Design enterprise-scale systems requiring collaboration among multiple engineers Make technical decisions and influence priorities and trade-offs that enable solutions to achieve short and long-term business objectives Take ownership of systems and designs that span multiple engineers’ work, breaking complex problems into smaller tasks for team members Champion new techniques and best practices across the organization, particularly around secure AI system design Act as a subject matter expert in one or more technical areas (e.g. AI security, identity and access management) Security & Identity Engineering Architect and implement identity and access management solutions for AI services, including authentication flows and fine-grained authorization Design service-to-service authentication patterns in cloud-native and AI service contexts Design and enforce security controls that protect AI systems against threats such as prompt injection, model inversion, and data exfiltration Define and implement compliance guardrails to meet regulatory and internal security standards (e.g. data residency requirements) Partner with security and compliance teams to perform threat modeling, security reviews, and penetration testing for AI platform components Establish security observability: audit logging, anomaly detection, and alerting for identity and authorization events Platform Development & Operations Design and implement complete AI platform solutions that integrate effectively with developer tools, cloud services, LLM providers, and observability systems Design deployment processes to minimize downtime with comprehensive alerting Understand trade-offs in different engineering processes and adjust team practices to meet project needs Lead resolution of difficult and complex operational incidents Team Leadership & Mentorship Mentor and coach junior engineers, providing guidance on technical approaches, security best practices, and career development Lead design reviews and provide actionable feedback to maintain a high bar for quality and security Take responsibility for challenging work that needs support, ensuring team success Work closely with product managers, data scientists, and cross-functional teams to align on requirements and strategy Facilitate cross-functional troubleshooting, root cause analysis, and vendor engagement when needed Quality & Excellence Lead the team in keeping code and systems well-designed, well-documented, and optimized Own team-level metrics, events, and documentation ensuring comprehensive observability Drive accountability for team-level application performance Ensure the team follows engineering and security standards; contribute to improving those standards Challenge the team to implement solutions that are robust, stable, scalable, and cost-effective

Requirements

7+ years of professional software engineering experience
Bachelor’s or Master’s degree in Computer Science or related field, or equivalent industry experience
Expert programming skills in Python with the ability to architect and deliver maintainable systems
Hands-on experience with IAM concepts, authentication protocols, and service authentication patterns
Hands-on experience with Kubernetes for container orchestration and production operations
Experience designing and deploying production systems on major cloud platforms, including infrastructure as code and reliability engineering
Proven ability to design large-scale systems requiring coordination across a full engineering team
Experience optimizing systems for performance, reliability, and cost-effectiveness
Strong analytical and debugging skills with ability to solve technical and business problems
Understanding of AI-specific security risks including prompt injection, model misuse, and data privacy, along with practical mitigation strategies
Familiarity with AI/ML concepts and technologies, including LLM orchestration frameworks, vector databases, or agentic platforms

Nice To Haves

CISSP, or equivalent security certification
2+ years of hands-on experience with security and identity solutions in production environments
Experience with secrets management platforms, key rotation strategies, and compliance frameworks

Responsibilities

Design enterprise-scale systems requiring collaboration among multiple engineers
Make technical decisions and influence priorities and trade-offs that enable solutions to achieve short and long-term business objectives
Take ownership of systems and designs that span multiple engineers’ work, breaking complex problems into smaller tasks for team members
Champion new techniques and best practices across the organization, particularly around secure AI system design
Act as a subject matter expert in one or more technical areas (e.g. AI security, identity and access management)
Architect and implement identity and access management solutions for AI services, including authentication flows and fine-grained authorization
Design service-to-service authentication patterns in cloud-native and AI service contexts
Design and enforce security controls that protect AI systems against threats such as prompt injection, model inversion, and data exfiltration
Define and implement compliance guardrails to meet regulatory and internal security standards (e.g. data residency requirements)
Partner with security and compliance teams to perform threat modeling, security reviews, and penetration testing for AI platform components
Establish security observability: audit logging, anomaly detection, and alerting for identity and authorization events
Design and implement complete AI platform solutions that integrate effectively with developer tools, cloud services, LLM providers, and observability systems
Design deployment processes to minimize downtime with comprehensive alerting
Understand trade-offs in different engineering processes and adjust team practices to meet project needs
Lead resolution of difficult and complex operational incidents
Mentor and coach junior engineers, providing guidance on technical approaches, security best practices, and career development
Lead design reviews and provide actionable feedback to maintain a high bar for quality and security
Take responsibility for challenging work that needs support, ensuring team success
Work closely with product managers, data scientists, and cross-functional teams to align on requirements and strategy
Facilitate cross-functional troubleshooting, root cause analysis, and vendor engagement when needed
Lead the team in keeping code and systems well-designed, well-documented, and optimized
Own team-level metrics, events, and documentation ensuring comprehensive observability
Drive accountability for team-level application performance
Ensure the team follows engineering and security standards; contribute to improving those standards
Challenge the team to implement solutions that are robust, stable, scalable, and cost-effective