Senior AI Engineer

Photon is building enterprise-ready AI capabilities with a focus on hands-on engineering, secure production delivery, and measurable business outcomes. This contract Senior AI Engineer role (hybrid in the United States) combines deep technical execution with standards, mentorship through code review, and collaboration across workstreams to help enable self-service AI solution delivery.

What you’ll do

• Design, build, and operate Tulip and related AI platform capabilities.
• Contribute to Tulip architecture, patterns, and technical standards so the platform scales securely and reliably across enterprise use cases.
• Deliver AI platform capabilities hands-on, including orchestration, RAG, agents, integrations, evaluation, observability, and production support patterns.
• Collaborate with engineers across workstreams to surface dependencies and risks early, and deliver assigned roadmap commitments predictably.
• Apply and help improve practices for secure, maintainable, testable, observable, and cost-conscious engineering execution.
• Contribute to documentation, design discussions, and knowledge sharing that strengthen how the team builds and operates AI solutions.
• Translate strategic AI objectives into technical outcomes that enable self-service solution delivery and measurable business value.
• Serve as a hands-on individual contributor with no people management responsibility, supporting roadmap execution through your own delivery and mentoring less experienced engineers through design discussion and code review.

Key success areas

• Platform architecture and engineering execution: architecture decisions, reusable patterns, design quality, and platform stability.
• AI capability delivery: shipped capabilities with production readiness and adoption by solution teams.
• Technical collaboration and roadmap contribution: roadmap visibility, predictable delivery, and early blocker resolution.
• Engineering excellence: code quality, testing coverage, operational health, and defect reduction.
• Knowledge sharing: improved team clarity, stronger handoffs, and repeatable delivery practices.
• Business alignment: stakeholder alignment, use case enablement, and business impact tracking.

Required 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 including 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 Azure, AWS, or GCP, including containerization and infrastructure as code (Docker, Kubernetes, Terraform, Helm), CI/CD, observability, and operational support for production services.
• Ability to translate business and product objectives into technical designs and executable engineering work.
• Demonstrated ability to contribute to technical design decisions and mentor less experienced engineers while working 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 for explaining complex technical decisions to engineering, product, and business stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (preferred) or equivalent practical experience.

Technologies you’ll work with

Python, large language models, retrieval-augmented generation, Docker, Kubernetes, Terraform, Helm, CI/CD, Azure, AWS, GCP, OAuth 2.0, OpenID Connect, secrets management, Azure AI, Azure OpenAI, Microsoft Fabric, Databricks, vector databases, semantic search, prompt orchestration, agentic AI frameworks, vector search, AI evaluation, multi-model integration, agent interoperability patterns, SQL.

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.

Compensation, contract details, and location

• Job type: contract (independent contractor).
• Location: United States (hybrid). Location expectations should be confirmed through the People and Talent process. Draft assumption: Tempe, Arizona / hybrid, aligned to current Client in-office guidance.
• Compensation: USD 56,000 to 196,000 per year. Compensation is based on actual experience and qualifications (good faith estimate).
• Post date rule: No applications will be considered if received more than 120 days after the date of this post.

Benefits

• Medical, vision, and dental benefits
• 401k retirement plan
• Variable pay/incentives
• Paid time off
• Paid holidays