Job Description

Senior Software Engineer – AI Platforms & Integrations

Greater Phoenix Area | Hybrid (4 Days Onsite)

AI-Native Product Engineering | Backend / APIs Focused

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.

What You’ll Be Doing

• 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, GitHub Copilot, etc.) to dramatically accelerate development velocity
• Review, refine, secure, and productionize 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

What They’re Looking For

• 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

Strongly Preferred Experience

• AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, 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, MuleSoft, 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

What Makes This Role Different

This team is specifically looking for engineers who have fundamentally changed how they build software because of AI.

That means:

• 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

Environment & Culture

• 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.

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