Top Software Engineer Jobs in Tucson, AZ

Develop and debug low-level embedded software for mission-critical drones and docking hardware. Responsibilities include Linux kernel development, device drivers, system bring-up, bootloader customization, BSP development, OS customization, firmware debugging, CI builds, and deploying stable operating system builds to physical devices. The role collaborates with electrical engineering, QA, cloud teams, internal stakeholders, and external partners to ensure hardware and software reliability.

Develop full-stack solutions using TypeScript and AWS cloud technologies. Responsibilities include building GraphQL APIs, business logic libraries, AWS Lambda functions with CDK, AWS Glue automation, and Angular/Ionic user interfaces. The engineer will also support CI/CD, Git repositories, linting, developer workflows, requirements management, and HIPAA-compliant software development. Collaboration with engineers, management, and business analysts is required.

Design, develop, and maintain scalable AI-forward APIs, MCPs, and services for Microsoft 365. Lead features from concept through launch, write reusable code, document designs, estimate work, and support production services through on-call responsibilities. Improve reliability, performance, and scalability while mentoring engineers and establishing technical best practices across teams.

Execute scheduled, ad hoc, and release-milestone software tests; review test cases; report defects in issue-tracking systems; communicate status in standups; and collaborate with software test managers and development teams. The role requires knowledge of QA methodologies, black-box, grey-box, and white-box testing, strong communication and organization, independent and team-based work, and participation in planning and professional meetings.

Design and deliver scalable control-plane and management services for Azure Storage at hyperscale. Lead architecture, reliability, and performance work for storage platforms that support AI workloads, adopt AI-assisted engineering practices, and own system health, incident response, and long-term technical roadmaps.

Design and build distributed storage systems optimized for AI and machine learning workloads at hyperscale. Lead architecture, development, testing, deployment, scalability, performance, security, and efficiency initiatives for zettabyte-scale Azure storage. Collaborate with AI researchers and cloud infrastructure teams, mentor engineers, evaluate emerging technologies, and solve complex problems involving availability, durability, replication, high-performance I/O, metadata, indexing, caching, and data placement.

Build and own backend, data architecture, and integrations for operations. Replace manual workflows with automations and AI agents, ship internal tools, ensure reliable data flows, monitoring, and documentation, and support production systems used by ops.

Own operations and reliability for hyperscale Azure GPU clusters and interconnect fabrics. Lead production incident triage, mitigation, recovery, root-cause analysis, and cross-stack debugging across hardware, GPUs, PCIe, firmware, drivers, and software. Develop automation, telemetry, diagnostics, playbooks, and escalation frameworks to improve observability, operational readiness, and mean time to mitigation for large-scale AI and HPC workloads.

Provides cross-functional architectural guidance across product areas, identifies technical risks and debt, makes design decisions, and translates architecture into executable engineering work. The role establishes coding and testing standards, mentors engineers, supports production applications, and owns build and release pipelines. The engineer also contributes to requirements, code reviews, security practices, automated testing, technical debt reduction, and reliable delivery across multiple codebases.

Senior engineer responsible for designing, building, and operating scalable data ingestion, processing, storage, and member-facing membership application. Drive architecture decisions, mentor engineers, build data pipelines, APIs, and ensure reliability, observability, CI/CD, and documentation while partnering with product and analytics stakeholders.

Lead design and implementation of the Libraries Platform: services, pipelines, and package index to build, verify, and serve secure reproducible libraries. Automate artifact creation, CVE remediation, SBOM/provenance generation, AI-assisted patching, and operate registry/mirroring, CI/CD integrations, reliability, observability, and incident response while mentoring engineers.

Design, implement, and maintain backend services and core APIs (primarily Scala). Collaborate on architecture, improve system reliability, and deliver production software for legal AI products.

Build and operate production custody systems: signing service, key management, chain integrations, and transaction pipelines. Own end-to-end subsystems, integrate new chains, collaborate with cryptography on threshold signing and key recovery, write post-mortems, and produce clear async design docs and PRs.

Pipeline for software engineering roles at multiple levels. Work may include design, development, testing of embedded or application software, firmware and hardware-software integration, code review, debugging, performance optimization, Agile/Scrum practices, and cross-functional collaboration with systems, controls, and hardware teams.

Serve as the senior technical engineer on a delivery team, writing production code, shaping architecture, mentoring engineers, diagnosing complex issues, and owning software quality and reliability. Build TypeScript and JavaScript applications using Node.js, Express, React, PostgreSQL, REST APIs, testing, and observability. Modernize legacy systems, manage integrations and data synchronization, and use AI tools and automation to improve engineering workflows and delivery.

Seeking a Senior Software Engineer with 5+ years of experience to design and develop large-scale distributed systems, mentor junior engineers, and manage complex projects in a dynamic setting.

Design, build, and maintain backend services in TypeScript for millions of users; develop full‑stack features with React/React Native; participate in code reviews; provide technical leadership, mentorship, and architecture guidance; collaborate with PM and design; use monitoring/metrics and Agile practices to deliver scalable, user-focused products.

Lead test architect for end-to-end integration testing of a complex genomics product portfolio. Design contract-first validations (OpenAPI/Avro), build resilient API and event-driven test frameworks, embed LLM-driven test generation and log analysis into CI/CD, mentor SQEs, enforce staging guardrails, and run chaos/resiliency experiments across distributed microservices.

Lead design and operation of a massively distributed edge compute platform using hyperscaler services and Kubernetes. Design external APIs, optimize L7 traffic routing, ensure high availability, fault tolerance, security and data privacy. Collaborate across AI/ML, hardware, network, and security teams, present scalability and reliability metrics to executives, mentor engineers, and establish architectural governance.

Lead Elasticsearch performance engineering from architecture through production. Develop performance models, optimize distributed systems, profile bottlenecks, build benchmarks, detect regressions, and improve scalability across stateful and serverless architectures. Design AI-assisted optimization and benchmarking tools, collaborate across teams, define performance strategies, and mentor engineers. The role requires deep Java, JVM, concurrency, distributed systems, and search or data-store performance expertise.

Develop and optimize Elasticsearch performance across distributed and serverless architectures. Responsibilities include implementing performance models, profiling systems, identifying bottlenecks, building benchmarks and regression detection, improving logging, metrics, vector search, and ES|QL performance, and creating AI-assisted optimization tools. The role also involves architectural and code-level optimization, technical analysis, peer reviews, and guidance for fellow engineers.

Lead strategic build-versus-buy engineering initiatives within Elastic’s IT organization. Design and deliver internal platforms using Elasticsearch, Kibana, Elastic ML, AI, and cloud technologies across developer productivity, FinOps, IT service management, and enterprise efficiency. Establish architecture and engineering standards, partner cross-functionally with IT, Security, Platform Engineering, Finance, and other teams, and validate Elastic products through internal production systems.

Develop and operate high-throughput, low-latency telemetry pipelines and cloud services for Azure AI/HPC infrastructure. Build observability, monitoring, analytics, and automation capabilities; own architecture through deployment and operations; and lead incident response, root-cause analysis, reliability improvements, and operational readiness. Partner across engineering and platform teams, influence technical roadmaps, mentor engineers, and apply distributed systems, AI infrastructure, and cloud operations practices at hyperscale.

Designs and implements protocols and features for highly scalable distributed block storage, focusing on durability, availability, performance, reliability, and observability. Responsibilities include coding, optimization, debugging, design documentation, stakeholder collaboration, incident response, on-call operations, and mentoring engineers. The role requires expertise in C or C++, distributed systems, cloud backend development, multithreaded programming, and large-scale software delivery.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.