Top Software Engineer Jobs

Own product surfaces end to end, spanning backend systems, APIs, user experience, deployment, observability, evaluations, and feedback loops. Work directly with AI companies and users to design products using models with memory. Prototype agentic products and internal tools, train models for demonstrations, develop telemetry and evaluations, collaborate with model researchers, and help establish product engineering standards.

Leads systems software prototyping and workload characterization for Azure hardware/software co-design. The role optimizes AI inference and LLM workloads, especially KV Cache placement, migration, and utilization across GPUs, CPUs, CXL memory, storage, and networks. Responsibilities include developing inference framework extensions, instrumentation, performance models, simulation frameworks, and memory-tiering proof-of-concepts while influencing long-term architecture and collaborating with hardware, software, workload, and industry partners.

The Chief Technology Officer leads application development, data and analytics, quality assurance, technology vendors, technical strategy, budgets, and digital transformation. The role partners with executives and the Head of AI to deliver technology initiatives, adopt emerging technologies, maintain governance and SOX compliance, establish performance metrics, and develop technology talent. The CTO oversees teams and ensures projects support business objectives, customer experience, operational efficiency, and long-term organizational growth.

Develops end-to-end core-system features, including AI-enabled functionality, testing, backend architecture, production monitoring, customer escalation management, code reviews, and collaboration with product managers to translate business requirements into scalable technical solutions.

Design and implement intelligent automation for AV software development, testing, release, and operational workflows. Build CI/CD pipelines integrating simulation and hardware-in-loop testing, develop engineering data pipelines and metrics, and create AI-enabled tools for test analysis, failure classification, defect triage, reporting, and workflow orchestration. Establish evaluation, governance, security, and monitoring standards for AI solutions while improving release readiness, software quality, engineering productivity, and cross-functional visibility.

Lead technical delivery for analytics-focused software: design, develop, test, and operate secure, high-quality production code. Drive automation and CI/CD, evaluate vendor/architecture choices, mentor junior engineers, and promote resilient cloud-native solutions within financial services technology teams.

The role involves leading the Observability Insights initiative at CoreWeave, focusing on developing APIs, agentic tools, and improving telemetry for AI systems. Candidates should possess significant experience in backend engineering and observability systems, especially for multi-tenant environments.

Build scalable AI capabilities for Fidelity Wealth as a senior full-stack engineer. Partner with business, product, architecture, data, and platform teams to create secure, reliable solutions. Responsibilities include prototyping, developing production-ready software, applying scalable design patterns, contributing to architecture discussions, practicing test-first development, and delivering high-quality solutions using modern programming languages and cloud platforms.

Build scalable AI capabilities for Fidelity Wealth as a full stack engineer. Partner with business, product, architecture, data, and platform teams to develop secure, reliable solutions. Responsibilities include prototyping, production software development, applying software design principles, testing, problem-solving, participating in design discussions, and delivering maintainable systems using modern programming languages, cloud platforms, and generative AI tools.

Build and maintain scalable full-stack integrations between Commure and healthcare systems, including EHRs and insurance providers. Design end-to-end workflows, use LLMs to reverse-engineer EHRs, improve architecture and reliability, troubleshoot production issues, implement monitoring, and ensure HIPAA, HL7, and FHIR compliance. Collaborate with product, healthcare, DevOps, QA, and security teams throughout development and deployment.

Build and operate full‑stack features for an AI-driven contract management platform. Collaborate with product, data science, and design; own services from development to production; mentor teammates; apply DevOps, CI/CD, containerization, and distributed systems best practices to scale AI capabilities.

As a Full Stack Engineer, you'll develop platform capabilities, collaborate with teams to implement solutions, and integrate new technologies while ensuring architecture and security are sound.

Lead full-stack engineering for Snowflake Snowsight, owning product areas end to end and driving large cross-team projects from architecture through delivery. Use agentic AI, Go, React, and Java to build scalable, reliable experiences. Partner with product and design, shape product vision, mentor engineers, establish technical standards, and improve customer experience, service health, performance, security, and quality.

GRVTY seeks students and recent graduates for 2027 internships and full-time roles across software engineering, AI, cybersecurity, data science, robotics, systems, electrical, and mechanical engineering. Candidates will build defense technology, contribute to complex software projects, and gain exposure to classified-environment deployments, government acquisition, and security frameworks. Applicants must be U.S. citizens pursuing or recently completing a relevant degree, available in 2027, and capable of learning quickly across multiple projects.

Participate in a paid remote interview about AI-assisted software engineering. Discuss your development workflow, use of coding assistants such as Copilot, Cursor, or Claude Code, model comparisons, debugging practices, prompt strategies, and challenges with generated code.

Design and build Kubernetes-based LLM serving infrastructure, including GPU scheduling, scaling, model lifecycle management, Helm packaging, enterprise and offline deployments, API integrations, and production observability. Develop across a multi-service Go codebase, contribute design documentation and reviews, and help guide engineering direction. The role requires strong Kubernetes, distributed systems, CI/CD, and infrastructure-as-code expertise, with GPU, inference, or adjacent systems experience.

Own product features end-to-end, including architecture, integrations, technical specifications, deployment, testing, and production reliability. Use AI agents as the primary development tool, delegate implementation, critically review generated code, and ensure financial transaction reliability. Work independently as an individual contributor while helping evolve the company’s AI-first development process.

Develop and optimize GPU-accelerated numerical linear algebra libraries for AI and high-performance computing. Design kernel generation, JIT compilation, matrix operations, and operator fusions; lead projects involving multiple engineers and teams; provide technical mentorship; collaborate with product management and customers on requirements and roadmaps; and improve performance and maintainability through architectural enhancements.

Build and ship end-to-end web features across UI, APIs, databases, tests, and deployment by directing AI coding agents. Translate requirements into agent-ready specifications, manage parallel agent sessions, review generated code, enforce security and quality, and require effective automated tests. Deploy and monitor applications on Azure, debug production issues, improve agent context and tooling, and document releases and operational procedures.

Design, build, and scale backend systems and microservices for automated chargeback and dispute workflows. Integrate with card networks, banks, and merchants, improve CI/CD, upgrade platform architecture, and own feature delivery and system optimizations.

Summer 2027 software engineering internship supporting AI/ML, big data, and cloud projects. The intern will collaborate with scientists, engineers, and project managers to develop, integrate, and deploy production-grade solutions in an agile, mission-oriented environment. Responsibilities include working with real-world datasets, enterprise-scale systems, multiple software components, and operational end users.

Designs, develops, debugs, and troubleshoots full-stack Java/Spring Boot microservices on AWS. Collaborates in Agile teams, applies CI/CD, works with Oracle and Kafka, uses enterprise AI-assisted coding tools, ensures secure, resilient, and scalable software, and contributes to engineering communities and best practices.

Leads a 45-person employee organization and 50 contractors responsible for USAA’s telematics application strategy, architecture, engineering delivery, vendors, budgets, security, compliance, and modernization. Oversees cloud, mobile, data, AI, machine learning, IoT, and connected-vehicle capabilities supporting insurance pricing, underwriting, claims, fraud detection, and member engagement. Partners with business and technology executives on roadmaps, technical debt reduction, SDLC controls, risk management, and ecosystem relationships.

Develops and maintains web applications for a government customer as part of an Agile team. Responsibilities include gathering requirements, writing software, implementing business logic, integrating web APIs, conducting unit and formal testing, troubleshooting production issues, performing impact analysis, supporting configuration control, and contributing to user training materials. The role uses HTML5, JavaScript, Bootstrap, CSS, C#.NET, SQL, Ruby on Rails, AWS, and AI technologies.

Develop and sustain cloud software and AI/ML capabilities for national security applications. Responsibilities include requirements analysis, Java-based distributed software development, AWS cloud integration, RESTful services, testing, deployment, troubleshooting, and technical documentation. The role works with Hadoop and big-data technologies, Linux, Kubernetes, infrastructure as code, CI/CD, LLMs, RAG, and agentic AI. An active TS/SCI clearance with polygraph and at least five years of software engineering experience are required.