Job Description
Senior Software Engineer – AI Platforms & Integrations
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📍 Greater Phoenix Area | Hybrid (4 Days Onsite)
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💡 AI-Native Product Engineering | Backend / APIs Focused
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🔄 6 Month Contract -Hire (no third parties- must be a US Citizen or GC Holder)
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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.
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This is not a traditional enterprise engineering role.
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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.
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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.
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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.
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What You’ll Be Doing
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- 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
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What They’re Looking For
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- 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
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Strongly Preferred Experience
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- 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
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What Makes This Role Different
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This team is specifically looking for engineers who have fundamentally changed how they build software because of AI.
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That means:
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- 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
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Environment & Culture
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- 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
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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.