Top Software Engineer Jobs in Ogden, UT

Build and operate large-scale data pipelines that collect, process, and optimize audio datasets for AI model training. The role involves discovering data sources, improving data quality, throughput, and cost efficiency, partnering with AI scientists, and owning engineering projects end to end. Strong backend software engineering, Python, Bash, Linux, production systems, and data-processing experience are required, with GCP, Terraform, web crawling, and audio or ML dataset familiarity preferred.

Build and operate large-scale AI data pipelines, discover audio data sources, optimize data-processing systems for quality, throughput, and cost, and collaborate with AI scientists on training datasets. The role requires backend software engineering, production systems experience, independent problem-solving, and ownership of projects from discovery through continuous improvement. Nice-to-have experience includes web crawling, distributed processing, cloud infrastructure, Terraform, dataset quality, and audio processing.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable ingestion and processing systems, optimizing data quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed, ambiguous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement, with emphasis on backend development, production systems, data acquisition, and scalable infrastructure.

Build and operate large-scale data pipelines that acquire, process, and optimize audio datasets for AI model training. Responsibilities include discovering data sources, improving data quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend engineering, production systems experience, and independent problem-solving in a distributed environment.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, optimizing processing systems for quality, throughput, and cost, and collaborating with AI scientists. Own engineering projects from discovery through continuous improvement while working independently in an ambiguous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires strong backend engineering, production systems experience, Python and Bash proficiency, and independent ownership of projects. Experience with web crawling, distributed processing, GCP, Terraform, machine-learning datasets, or audio processing is advantageous.

Build scalable data pipelines and processing systems for AI model training at petabyte scale. Responsibilities include discovering audio data sources, improving dataset quality and processing efficiency, optimizing throughput and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, optimizing data processing for quality, throughput, and cost, partnering with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and scale full-stack software for employer and Employee Assistance Program products, including employer portals, patient and provider workflows, eligibility, authorization, and billing. Lead technical projects, design secure distributed systems, mentor engineers, contribute to engineering culture, and use modern technologies and AI-assisted development tools. Collaborate cross-functionally to expand access to mental healthcare.

Build and scale full-stack software for an AI-native cybersecurity platform. Responsibilities include developing backend services and APIs, creating frontend applications, collaborating on product features, writing tested code, participating in reviews, troubleshooting across the stack, and improving engineering processes. The role requires 3–5 years of software engineering experience and experience with backend, frontend, databases, and cloud technologies. Docker, Kubernetes, CI/CD, AI/ML, and startup experience are preferred.

Join as the founding full-stack engineer to extend a TypeScript React/Next.js prototype, design product features, integrate AI/OCR, write tests and infrastructure, talk to users, and iterate quickly to drive growth.

Build and maintain high-performance, resilient SDKs across multiple programming languages and platforms. Develop features, improve reliability, collaborate with engineering and product teams, maintain open-source repositories, and influence technical and product decisions. The role requires strong software engineering fundamentals, polyglot development ability, library-building experience, production-quality coding, and expertise in unit, integration, load testing, and benchmarking.

Work directly with the founder to design and build core product features: integrations that pull license data, automation to file renewals/applications, data cleaning with AI, dashboard and alerting UX, and establish engineering practices for testing, deployments, and security. Term contractor role with potential conversion to full-time based on performance.

Build, test, review, deploy, monitor, debug, and maintain full-stack software used in K-12 classrooms. Work primarily with React, TypeScript, Node.js, and AWS while improving complex codebases and service design. Participate in incident response, refactoring, code reviews, pairing, mentorship, and cross-functional collaboration with product, design, and education experts. Use AI tools thoughtfully and prioritize reliable, accessible, and equitable learning experiences.

Lead end-to-end development of reliable care-agent tooling and software services integrating contact-center platforms with backend systems. Own architecture, performance, security, production operations, and technical direction while partnering with product, care operations, QA, and engineering teams. Translate operational workflows into scalable solutions, mentor engineers, and improve tools using agent feedback, operational metrics, and AI-assisted development practices.

Develop and maintain scalable cloud- and edge-based software, including user-facing applications, APIs, distributed services, and supporting systems. Own software components, apply test-driven development, conduct code reviews, improve performance and security, and contribute to complex technical projects. Collaborate with cross-functional teams to design, deploy, and scale early-stage healthcare products across cloud and on-premises environments.

Build and scale backend systems, APIs, infrastructure, and applications for multimodal sensing and AI intelligence platforms. Responsibilities include processing sensor, audio, video, and environmental data; supporting data pipelines and model inference; ensuring reliability, scalability, and data integrity; and contributing to engineering standards and long-term technical strategy.

Lead technical vision and strategy for Affirm’s Cards backend engineering organization. Architect scalable and reliable platforms, guide cross-team initiatives, champion AI adoption and engineering excellence, influence technical roadmaps, and mentor engineers through Staff level. The role requires strong architectural expertise, organizational leadership, project management, communication, and cross-functional collaboration.

Lead design and build of production-ready cloud and AI systems, prioritize security and reliability, ship solutions quickly using modern engineering practices, collaborate with cross-functional teams, mentor engineers, drive customer adoption, and deliver reusable assets and end-to-end complex deliveries.

Design and implement experiments in browser engine subsystems, investigate DOM, layout, rendering, navigation, events, and execution behavior, and evaluate performance, correctness, and compatibility. Prototype new engine capabilities, instrument and profile browser behavior, develop repeatable tests, document results, and optimize validated improvements. Collaborate with technical leadership while using AI coding and analysis tools and verifying outputs through debugging, testing, and measurement.

Leads the design and implementation of highly scalable Azure messaging and PubSub services. Defines architecture, testing strategies, coding standards, and reusable engineering frameworks; mentors engineers and conducts design and code reviews. Drives incident response, root-cause analysis, service reliability, SLA compliance, and operational improvements. Partners with stakeholders and customers to shape requirements and product direction, while advancing responsible AI practices throughout the software development lifecycle.

Develop and debug production-grade full-stack applications across front-end and back-end systems. Build features, APIs, databases, and data models; troubleshoot end-to-end issues; analyze unfamiliar codebases; translate implementations across programming languages; and review AI-generated and developer-written code for correctness, security, scalability, performance, and maintainability.

Develop and evaluate coding tasks for AI systems, including bug fixes, feature development, refactoring, optimization, reproducible environments, reference solutions, automated testing, and deterministic evaluation. The role also involves debugging complex codebases, reviewing contributions, documenting technical decisions, and refining evaluation criteria. Candidates should have strong software engineering fundamentals, backend or API development experience, open-source contributions, and proficiency in at least one listed programming language.

Principal Software Engineer leading architecture and hands-on development for Swiftly’s multi-tenant ads and martech platform. Responsibilities include designing distributed systems, migrating legacy services without downtime, optimizing a low-latency Go ad server, defining database and service contracts, integrating ad-tech platforms, operating Azure production services, and setting engineering quality standards across testing, observability, CI/CD, security, and infrastructure.