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Nextiva

Staff AI Engineer

Nextiva

. Build an internal AI platform shaping work across engineering and the broader organization .

Posted 10/16/2026full-timeScottsdale • Arizona • United StatesLead💰 $115,000 - $205,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and delivering production-grade AI systems and workflows, with a strong focus on cloud-native solutions in GCP and AWS. Proven ability to influence technical direction and improve developer productivity through innovative AI applications and automation.

Highest-signal resume keywords
AI/ML Solution DevelopmentCloud-Native Architecture (GCP/AWS)Software Architecture and System DesignDevOps and CI/CD PracticesTechnical Leadership and Mentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
JavaPythonGoAI/ML FrameworksLarge-Scale Systems DesignObservability and MonitoringInfrastructure as CodeSecurity Best PracticesSoftware Development Lifecycle (SDLC)Automation Opportunities Identification
Soft Skills
Technical JudgmentCross-Functional InfluenceProblem-SolvingCollaborationMentorship
Industry Keywords
Agentic AIGenerative AIProduction-Scale SystemsDeveloper ProductivityEnterprise Automation

Tech Stack

Tools & technologies
AWSCloudGoogle Cloud PlatformJavaPythonSDLCGo

About the role

Key responsibilities & impact
  • Build an internal AI platform shaping work across engineering and the broader organization
  • Architect and deliver production-grade agentic AI workflows across the software development lifecycle
  • Develop reusable architecture, services, infrastructure, patterns, and guardrails for secure, observable production-scale AI workflows
  • Identify and execute high-value automation opportunities across engineering and business processes
  • Architect, build, deploy, and operate production-grade AI systems and agentic workflows
  • Design scalable internal platform capabilities for safe AI-powered automation adoption
  • Own solutions end-to-end from problem definition and architecture through implementation, deployment, observability, security, scaling, and operation
  • Integrate AI models, agents, developer tooling, internal platforms, enterprise systems, APIs, data sources, and engineering workflows
  • Apply software engineering principles including modular architecture, testing, reliability, performance, maintainability, and fault tolerance
  • Design AI evaluation, observability, quality measurement, failure handling, and continuous improvement approaches
  • Make architectural and technology decisions based on business outcomes, engineering constraints, risk, and total cost of ownership
  • Design and operate cloud-native production workloads in GCP and/or AWS
  • Partner with infrastructure, DevOps, security, architecture, and engineering teams on reusable patterns, standards, and operational guardrails
  • Identify opportunities to improve developer workflows across the end-to-end SDLC
  • Evaluate emerging AI models, frameworks, agent architectures, and developer technologies
  • Provide Staff-level technical leadership through architecture reviews, design decisions, technical mentorship, and cross-team influence
  • Translate ambiguous business and engineering problems into technical strategies and measurable solutions

Requirements

What you’ll need
  • 10+ years of professional software engineering experience designing, building, and operating complex production-scale systems
  • Hands-on experience designing and building AI/ML or generative AI solutions that reached production and/or delivered measurable business outcomes
  • Strong software architecture and system design skills for distributed or large-scale systems
  • Strong programming and software engineering fundamentals in Java, Python, Go, or equivalent
  • Hands-on experience with LLMs, generative AI, AI agents, or AI-enabled application architectures
  • Experience taking AI solutions into deployment, operationalization, monitoring, security, reliability, and scale
  • Deep hands-on experience with GCP and/or AWS designing and operating cloud-native production systems
  • Strong understanding of DevOps, CI/CD, infrastructure as code, observability, reliability, and production operations
  • Strong understanding of application, infrastructure, data, and AI security considerations
  • Strong understanding of the end-to-end software development lifecycle, developer workflows, and large software systems/codebases
  • Ability to evaluate technical trade-offs and select maintainable technologies based on business outcomes and operational requirements
  • Strong technical judgment in ambiguous, cross-functional problem spaces
  • Ability to influence technical direction across teams without relying solely on organizational authority
  • Preferred: experience with agentic AI systems, multi-step AI workflows, tool-using agents, or autonomous/semi-autonomous engineering workflows
  • Preferred: experience applying AI to developer productivity, code generation, testing, code review, incident management, or other SDLC stages
  • Preferred: experience building internal developer platforms, engineering productivity platforms, or enterprise automation capabilities
  • Preferred: experience with AI evaluation frameworks, model/agent observability, prompt and context management, retrieval architectures, and production AI quality measurement
  • Preferred: experience spanning traditional software engineering and AI engineering
  • Preferred: experience driving technical initiatives across multiple teams, systems, or organizational domains

Benefits

Comp & perks
  • Multiple health plan options including medical, dental, vision, and telemedicine coverage
  • Life, disability, and supplemental indemnity plans
  • Flexible Time Off for salaried employees
  • PTO for hourly employees
  • Paid Sick Time
  • Paid Parental Bonding Leave
  • Holiday pay
  • 401(k) with company match
  • Health Savings Accounts with company contributions
  • Dependent Care FSA
  • Employee Assistance Program (EAP)
  • Comprehensive wellness initiatives
  • Ongoing learning and development opportunities
  • Career advancement opportunities