Top Artificial Intelligence Software Engineer Jobs in Phoenix – Mesa – Scottsdale, AZ

Build full-stack features for AI voice and chat products that scale to millions of conversations. Integrate ASR/TTS and conversational models, optimize production systems for latency and cost, participate in on-call rotations, and collaborate with product and ML teams to improve performance and user experience.

Build and operate an AWS-native data lake and AI gateway. Implement and maintain lakehouse architecture (Iceberg) using Glue, Athena, and S3; manage infrastructure as code (Terraform); run reliable data pipelines; operate LLM gateway/Bedrock; enforce security, IAM, networking, and secrets controls; partner with IT and Security.

Design, implement, and operate region-spanning, low-latency distributed systems and observability for LiveKit Cloud. Build resilient architectures, libraries, protocols, and tooling; diagnose and harden critical paths using metrics, tracing, testing, and production traffic insights.

Evaluate and solve real-world backend, full-stack, systems, and infrastructure engineering tasks. Review, debug, and improve code across environments; design and assess APIs, databases, services, testing, and deployment workflows; identify tradeoffs around scalability, reliability, performance, security, and developer experience; communicate technical reasoning clearly and collaborate with customer teams.

Provide expert software engineering to improve and optimize codebases used for AI training: bug fixes, feature development, refactoring, performance tuning, architecture recommendations, documentation, and cross-functional collaboration to support scalable AI training workflows.

Design, build, and configure Amazon Connect contact flows and IVR experiences; develop AWS Lambda functions and Lex bots; configure Contact Lens and CTRs; integrate Connect with CRMs (Salesforce, ServiceNow) and third-party APIs; monitor via CloudWatch; support IaC deployments (CloudFormation/Terraform); document designs and support UAT with stakeholders.

Hands-on engineering leader who writes and reviews production code while managing a small team. Architects scalable systems, drives engineering and product strategy, improves developer workflows, supports pre-sales and integrations, defines KPIs, and partners cross-functionally to deliver high-quality SaaS products with evolving AI capabilities.

Build and own the GTM tech stack and integrations, create demo environments seeded with realistic data, embed AI agents into sales workflows, stand up revenue data infrastructure (pipeline, forecasting, attribution), and automate customer service flows. Partner closely with Sales, Marketing, Customer Success, and Product Engineering to measure adoption and impact.

Create video content, present at webinars and conferences, write sample code and documentation, review others' content, and respond to audience questions to educate and promote the product.

Design, build, and maintain AI-powered B2B SaaS products across frontend, backend, and AI. Own projects end-to-end, collaborate with product and design, ensure maintainability, mentor teammates, and inform roadmap and implementation decisions.

Design, enhance, and maintain backend APIs and integrations for the VA Beneficiary Travel Self-Service System. Implement secure, performant services for automated claim processing, collaborate in two-week agile sprints, support CI/CD and zero-downtime deployments, perform testing, documentation, code reviews, troubleshoot production issues, and ensure compliance with VA standards including security and 508 accessibility.