Senior AI Engineer_Tempe, AZ

* Position Overview

Client is investing in enterprise AI capabilities to accelerate delivery,

enable self-service technology, and help teams solve meaningful business

problems faster. Tulip is a strategic AI platform that provides reusable

patterns, tools, and services to make AI-enabled solution delivery easier,

safer, and more scalable across the organization.

The Senior AI Engineer - Tulip Platform is a hands-on role responsible for

designing, building, and operating Tulip and related AI platform

capabilities. The focus is deep technical execution: contributing to

architecture and engineering standards, and mentoring peers through design

discussion and code review.

The ideal candidate is a pragmatic builder and strong technical partner who

can navigate ambiguity, uphold clear technical standards, and consistently

deliver high-quality AI solutions aligned to business priorities.

Job Qualifications

* 8+ years of professional software engineering experience with increasing

responsibility for architecture, platform delivery, or complex enterprise

systems.

* Hands-on experience designing and delivering production-grade

applications, APIs, integrations, and distributed services.

* Strong proficiency in Python and modern software engineering practices

such as automated testing, code review, and maintainable design.

* Experience with AI-enabled systems, including large language models,

retrieval-augmented generation, agent or workflow orchestration patterns,

model integration, evaluation, and responsible AI guardrails.

* Experience with cloud platforms such as Azure, AWS, or GCP, including

containerization and infrastructure as code (Docker, Kubernetes,

Terraform, Helm), CI/CD, observability, and operational support for

production services.

* Experience translating business and product objectives into technical

designs and executable engineering work.

* Demonstrated ability to contribute to technical design decisions, mentor

less experienced engineers, and work effectively across multiple

workstreams.

* Experience securing enterprise services and AI integrations, including

OAuth 2.0 and OpenID Connect, secrets management, and automated security

scanning in CI/CD.

* Strong communication skills with the ability to explain complex technical

decisions to engineering, product, and business stakeholders.

* Bachelor's degree in Computer Science, Engineering, Information Systems,

or related field preferred, or equivalent practical experience.

Preferred Qualifications

• * Experience building internal developer platforms, enterprise AI platforms,
• automation frameworks, or reusable engineering accelerators.
• * Experience with Azure AI, Azure OpenAI, Microsoft Fabric, Databricks,
• vector databases, semantic search, prompt orchestration, or agentic AI
• frameworks.
• * Experience with enterprise AI governance, model and prompt auditability,
• and responsible AI controls in a compliance-sensitive environment.
• * Experience enabling citizen development, self-service workflows, or
• governed low-code/no-code solution delivery.
• * * Experience working in retail, restaurant, ecommerce, loyalty, finance,
• supply chain, or high-volume enterprise environments.
• * Experience partnering with product managers, business analysts, forward
• deployed engineers, and enterprise architects to move ideas from discovery
• to delivery.
• Skills
• * AI platform architecture and engineering execution
• * LLM, RAG, agentic workflows, vector search, AI evaluation, multi-model
• integration, and agent interoperability patterns
• * API, integration, eventing, and data architecture
• * Containers, Kubernetes, and infrastructure as code
• * Python, SQL, cloud-native engineering, and secure service design
• * Spec-driven development and AI-augmented engineering workflows
• * Technical sequencing, dependency awareness, and predictable delivery
• * Engineering standards, design reviews, and code quality
• * Production readiness, service reliability, SLOs, incident response, and
• cost awareness
• * Peer mentorship, cross-team collaboration, and stakeholder communication
• Key Result Areas (KRAs)
• These KRAs describe the primary outcomes expected from this role and how
• success will be evaluated.
• Platform Architecture and Engineering
• Expected Outcomes: Contribute to Tulip architecture, patterns, and technical
• standards so the platform can scale securely and reliably across enterprise
• use cases.
• Example Measures: Architecture decisions, reusable patterns, design quality,
• platform stability
• AI Capability Delivery
• Expected Outcomes: Deliver AI platform capabilities hands-on, including
• orchestration, RAG, agents, integrations, evaluation, observability, and
• production support patterns.
• * Example Measures: Delivered capabilities, production readiness, adoption by
• solution teams
• * Technical Collaboration and Roadmap Contribution
• * Expected Outcomes: Collaborate with engineers across workstreams, surface
• dependencies and risks early, and deliver assigned roadmap commitments
• predictably.
• * Example Measures: Roadmap visibility, delivery predictability, blocker
• resolution
• * Engineering Excellence
• * Expected Outcomes: Apply and help improve practices for secure, maintainable,
• testable, observable, and cost-conscious engineering execution.
• * Example Measures: Code quality, testing coverage, operational health, defect
• reduction
• * Engineering Practices and Knowledge Sharing
• * Expected Outcomes: Contribute to documentation, design discussions, and
• knowledge sharing that strengthen how the team builds and operates AI
• solutions.
• * Example Measures: Improved team clarity, stronger handoffs, repeatable
• delivery practices
• * Business Alignment and Value Realization
• * Expected Outcomes: Translate strategic AI objectives into technical outcomes
• that enable self-service solution delivery and measurable business value.
• * Example Measures: Stakeholder alignment, use case enablement, business impact
• tracking
• * Ways of Working
• * This role is a hands-on individual contributor with no people management
• responsibility. The Senior AI Engineer contributes to technical decisions,
• supports roadmap execution through their own delivery, mentors less
• experienced engineers, and models practices that improve quality, velocity,
• and consistency. Success requires deep technical execution paired with clear
• communication across product, architecture, engineering, and business
• partners.
• * Location Requirement
• * Location expectations should be confirmed through the People and Talent
• process. Draft assumption: Tempe, Arizona / hybrid, aligned to
• current Client in-office guidance.
• * Physical Requirements / Work Environment
• * This position primarily operates in a professional office or remote work
• environment and routinely uses standard office equipment. Reasonable
• accommodations may be made to enable individuals with disabilities to perform
• the essential functions.
• Compensation, Benefits and Duration
• Minimum

Compensation

USD 56,000

Maximum

Compensation

USD 196,000

Compensation

is based on actual experience and qualifications of the

candidate. The above is a reasonable and a good faith estimate for the role.

Medical, vision, and dental benefits, 401k retirement plan, variable

pay/incentives, paid time off, and paid holidays are available for full time

employees.

This position is available for independent contractors

No applications will be considered if received more than 120 days after the

date of this post