Senior Software Engineer; AI

Senior Software Engineer – AI Platforms & Integrations

6 Month Contract - Hire (no third parties - must be a US Citizen or GC Holder)

We are partnered with a rapidly growing company building an enterprise AI platform designed to power intelligent workflows, knowledge retrieval, automation, and AI-enabled operational experiences across a large-scale business environment.

This is not a traditional enterprise engineering role.

The team is looking for a highly technical, AI-native engineer who thrives in ambiguity, moves quickly, and can operate with significant autonomy in a fast-moving environment. This person will play a critical role in building production-grade AI integrations, orchestration layers, internal tooling, and backend services that sit at the center of the company’s next-generation AI initiatives.

The ideal candidate is deeply hands-on, highly product-minded, and already leveraging modern AI tooling as part of their day-to-day engineering workflow.

This role is heavily backend and API focused. While full-stack exposure is helpful, the priority is someone strong in backend architecture, integrations, cloud services, orchestration, and enterprise system connectivity.

• Build and scale AI-enabled internal platforms, orchestration services, and automation workflows
• Develop backend services, APIs, integrations, and agentic workflows that interact with enterprise systems and AI tooling
• Design systems that leverage LLMs, retrieval pipelines, tool-calling, workflow automation, and enterprise knowledge access
• Integrate with platforms such as HR systems, support tooling, communication platforms, CMS systems, operational tooling, and data platforms
• Rapidly prototype and ship production-ready AI-powered applications and workflows
• Use AI-assisted engineering tools (Cursor, Claude Code, Git Hub Copilot, etc.) to dramatically accelerate development velocity
• Review, refine, secure, and product ionize AI-generated code and workflows
• Partner directly with technical and business stakeholders to translate ambiguous problems into scalable solutions
• Help define engineering patterns, architecture standards, and AI governance best practices
• Contribute across architecture, backend engineering, integrations, observability, CI/CD, testing, and cloud infrastructure

• 7+ years of software engineering experience
• Strong backend engineering experience building APIs, integrations, distributed services, and cloud-native systems
• Experience building real-world AI-enabled applications, integrations, or internal AI tooling
• Hands-on experience with modern AI engineering workflows and AI-assisted development tooling
• Ability to operate independently in a high-autonomy, startup-style environment
• Experience working directly with stakeholders and owning projects end-to-end
• Strong understanding of system design, security, testing, observability, and maintainability
• Experience integrating with enterprise platforms, third-party APIs, event-driven systems, or iPaaS tooling
• Cloud experience, ideally AWS
• Comfortable moving quickly while maintaining production-quality standards
• Strong written and verbal communication skills

• AI orchestration frameworks such as Lang Chain, Lang Graph, Semantic Kernel, CrewAI, Auto Gen, or similar
• Experience with agentic workflows, tool-calling, MCP, function-calling, or AI-to-system integrations
• RAG architectures, vector databases, embeddings, or enterprise knowledge retrieval
• AWS Bedrock or other enterprise LLM platforms
• Integration tooling such as Workato, Mule Soft, Boomi, or similar
• Experience building AI workflows connected to operational, support, HR, or enterprise systems
• Exposure to Datadog, Snowflake, Zendesk, Workday, Microsoft Teams, or similar enterprise tooling

• Using AI tools as part of real engineering workflows — not just experimentation
• Writing strong specs, prompts, implementation plans, and validation criteria
• Leveraging AI to increase velocity while still maintaining engineering rigor
• Owning architecture, quality, security, and production readiness
• Understanding where AI accelerates engineering — and where human judgment still matters most
• Fast-moving, highly collaborative engineering environment
• Significant ownership and autonomy
• Small, high-impact team with strong technical expectations
• Builders and problem-solvers thrive here
• Hybrid schedule with 4 days/week onsite in the Greater Phoenix area

This is an opportunity to help shape how a large-scale organization operationalizes AI across the business while still working in an environment that feels highly entrepreneurial and engineering-driven.