Top Software Engineer Jobs

Build and lead full-stack software engineering projects using Java, Python, cloud platforms, microservices, databases, containers, and AI-enabled development tools. Provide technical leadership across Agile teams, define service architectures and integration patterns, improve system performance, reduce technical debt, establish engineering standards, mentor developers, and deliver secure cloud-based solutions supporting enterprise and regulatory needs.

Provides principal-level technical leadership for digital products, applications, and AI/ML-enabled platforms supporting the CFO organization. Responsibilities include architecture, design and code reviews, prototyping, troubleshooting, engineering standards, and hands-on development using modern application and platform technologies. The role partners with data and ML engineers on forecasting and predictive analytics, mentors engineers, influences technical direction, and advances scalability, observability, security, and production engineering practices.

Leads Clever’s engineering organization and technical strategy, overseeing architecture, execution, production systems, organizational design, recruiting, and leadership development. The role remains technically hands-on through architecture and code reviews, debugging, production support, and direct contribution. It also drives AI-assisted engineering, modernization of legacy systems, engineering productivity, and close collaboration with Product and executive leadership.

Lead design and development of enterprise software solutions using Java and Cursor AI. Provide technical leadership, mentor engineers, define architecture and roadmaps, implement cloud-native, microservices, CI/CD and infrastructure-as-code practices, and collaborate across product and engineering teams to deliver performant, secure systems.

Designs and leads globally distributed AI infrastructure that routes, prioritizes, and allocates computing capacity for Azure OpenAI and Microsoft Copilot. Responsibilities include coding, architecture, capacity optimization, reliability engineering, incident response, secure deployments, cross-team delivery, mentoring, and operating highly available services. The role also advances AI-assisted software development and responsible AI practices.

Build and operate backend services, batch and real-time data pipelines, document-processing systems, APIs, integrations, and data models supporting an AI platform. Develop reliable OCR and LLM workloads, data quality monitoring, secure exports, cloud infrastructure, and CI/CD workflows. Design for distributed-system failures, authentication, authorization, and sensitive-data protection. Contribute to architecture decisions, maintain legacy services, support internal tools, mentor junior engineers, and improve engineering standards.

The role involves developing and enhancing a revenue cycle management platform, ensuring efficient data access for healthcare providers, and collaborating with clients to address their needs.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Leads architecture and technical strategy for the Arena SaaS platform. Responsibilities include designing distributed systems, improving scalability, reliability, security, and developer productivity; leading complex initiatives across engineering teams; driving modernization; evaluating emerging and AI-enabled technologies; mentoring senior engineers; and partnering with Engineering and Product leadership. The role requires hands-on Java expertise and strong experience with enterprise SaaS platforms, APIs, cloud-native architectures, and technical influence across multiple teams.

Define Scribd’s technical vision for agentic engineering and establish architecture, patterns, and guardrails for AI-assisted software development. Lead internal developer tools, libraries, platforms, and engineering workflow improvements across codebases, CI/CD, and infrastructure. Partner with engineering leadership on ambiguous cross-organizational initiatives, mentor senior and staff engineers, and drive adoption of coding-agent capabilities throughout the organization.

Lead a small autonomous engineering team combining experienced developers with AI coding agents. Own architecture, technical direction, software implementation, delivery, quality, security, reliability, and production operations. Establish AI-assisted engineering workflows, testing and deployment guardrails, and scalable development practices. Mentor two engineers, translate business objectives into technical solutions, resolve blockers, and continuously improve engineering productivity and software quality through hands-on leadership.

Build, test, deploy, and support production software, including product features, APIs, integrations, and internal tools. Use AI coding agents such as Claude Code and OpenAI Codex to accelerate development while reviewing generated code for correctness, security, and performance. Write automated tests, debug issues, participate in code reviews, maintain documentation, and own features through production readiness. Collaborate with engineers, clarify requirements, and continuously improve software delivery practices.

Build and operate scalable AI platform infrastructure enabling secure, reliable access to foundation models and AI agents. Responsibilities include developing model gateways, provider integrations, routing, usage controls, observability, governance, and self-service platform capabilities. The role involves architecting distributed systems, improving reliability and security, collaborating across engineering and product teams, mentoring engineers, and establishing high-quality engineering practices.

Evaluate AI coding-agent interactions for usefulness, correctness, engineering judgment, reasoning quality, and developer trust. Provide clear, opinionated feedback, distinguish response-quality levels, and help define standards for excellent interactions with tools such as OpenAI Codex, Claude Code, and Cursor. This contract role requires staff- or principal-level software engineering experience and familiarity with modern AI-assisted development workflows.

Architect and operate Cisco’s AI Compute Platform, developing distributed control-plane services, Kubernetes platforms, GPU schedulers, APIs, controllers, and automated remediation systems. The role manages multi-cluster environments, tenant quotas, workload routing, GPU allocation, and reliability for large-scale training and inference workloads. It also leads architecture reviews, establishes engineering standards, mentors engineers, and drives Infrastructure as Code, GitOps, CI/CD, observability, incident response, and operational excellence.

Build Orpex’s AI workforce platform end-to-end as a founding engineer, member of technical staff, or applied AI engineer. Responsibilities include defining product outcomes, developing and deploying production software, speaking with users, iterating quickly, handling infrastructure and UI work, and supporting hiring. The role begins in Vienna and requires relocation to San Francisco by January 2027. Visa sponsorship and relocation support are provided.

Leads and develops an infrastructure, operations, and shared-platform engineering team supporting Microsoft Monetize’s high-scale real-time advertising platform. Owns roadmap, architecture, delivery, reliability, and operational excellence across hybrid Azure and on-premises environments. Guides low-latency C/C++ services, distributed caching, streaming pipelines, model-backed serving, traffic management, infrastructure modernization, CI/CD, observability, incident response, and developer productivity while partnering across engineering, product, machine learning, and infrastructure teams.

Design and evolve cloud-native services, distributed systems, and infrastructure platforms at scale. Lead architecture and technical direction across compute, networking, storage, AI infrastructure, HPC, GPU environments, and datacenter systems. Improve automation, observability, reliability, security, CI/CD, and developer productivity while collaborating across engineering organizations. Mentor engineers and contribute to architecture reviews and operational excellence for large-scale production platforms.

Lead the reliability and scaling of Horizon AI’s autonomous platform for production GPU infrastructure. Harden agent dispatch with circuit breakers, retries, health-aware routing, and observable error handling. Build caching and event-streaming capabilities, determine and implement the orchestration strategy, introduce infrastructure as code, enable concurrent agent sessions, and own service standards, testing, CI, observability, and deployment practices. Serve as technical deputy and collaborate with Systems and SRE teams.

Designs, develops, tests, troubleshoots, and maintains secure, scalable software solutions using Java, with exposure to React and AWS. Creates architecture and design artifacts, supports application resiliency and CI/CD, analyzes data to improve systems, and uses enterprise-authorized AI-assisted development tools while validating outputs for correctness, performance, and security.

Develop AI agents and secure MCP servers for IAM and enterprise applications. Build Python and Node.js backend services, REST APIs, and modern React or Vue.js interfaces. Integrate LLMs and generative AI into existing workflows while applying prompt engineering, tool integration, security, scalability, and performance best practices. Collaborate with engineering and product teams to deliver AI-powered enterprise solutions.

Build backend services, data pipelines, APIs, distributed systems, developer tools, and shared platform capabilities for AI products. Develop ML experiment tracking, artifact management, and automated training and evaluation pipelines. Improve reliability, latency, and throughput while collaborating with Product and ML teams. Own scoped projects involving implementation, testing, maintenance, and clean API design for enterprise and government customers.

Develops secure, scalable software solutions for JPMorganChase Asset Management. Responsibilities include architecture and application development, production coding, troubleshooting, database optimization, cloud deployment, event processing, infrastructure automation, and responsible use of AI-assisted development tools. The engineer also analyzes data, creates technical artifacts, supports application resiliency and security, and contributes to agile team practices and reusable engineering patterns.

Build and ship end-to-end product features, debug and resolve production issues, partner with Product on UX and direction, use AI heavily for development and prototyping, and iterate quickly across the stack to improve quality and speed.

Design, develop, and support enterprise Java applications, microservices, REST and SOAP APIs, and cloud-native AWS solutions. Integrate and operationally support LLM and agentic AI capabilities, including retrieval-augmented generation, vector search, evaluation, guardrails, and monitoring. Build automated tests, participate in architecture and customer discussions, address security and code quality issues, provide production support, and mentor junior and mid-level developers.