Top Software Engineer Jobs

Lead and scale MEDHOST’s software engineering organization, overseeing product delivery, modernization, security, reliability, scalability, and operational performance. Develop technology strategy and architecture roadmaps while driving AI-first transformation across products, engineering workflows, and enterprise operations. Establish performance metrics, govern technology investments, manage strategic initiatives, and advise executives on emerging technologies, risks, and opportunities. The role also requires implementing generative AI, machine learning, and AI governance within healthcare software environments.

Architect and deploy distributed simulation environments for aerospace systems and constellation-level modeling. Build data pipelines to process, analyze, and visualize large simulation datasets; derive engineering and mission insights through statistical analysis and data modeling; optimize HPC and cluster infrastructure; translate mission requirements into scalable architectures; and integrate complex simulation ecosystems across subsystems and analytical tools.

Build and operate MeritFirst’s assessment and hiring platform, including candidate and employer experiences, assessment delivery and evaluation systems, workflows, infrastructure, and AI-enabled features. Own problems end to end from product discovery and system design through deployment, debugging, observability, and iteration. Develop reliable, interpretable, auditable, secure, privacy-conscious software, improve technical foundations, and help establish engineering standards as the company scales.

Develops and maintains web applications for a government customer within an Agile team. Responsibilities include requirements analysis, software design and coding, business logic implementation, API integrations, unit and formal testing, configuration change control, production troubleshooting, cost estimation, impact analysis, and user training support. The role uses front-end and back-end technologies, AWS cloud services, and collaboration with analysts, UI/UX developers, testers, project leads, and customers.

Provides senior technical leadership across a broad application portfolio, driving engineering modernization, cloud and API adoption, application optimization, AI-assisted delivery, and DevSecOps practices. Partners with business and technology stakeholders on roadmaps and scalable solutions, influences cross-functional technical decisions, mentors engineers, evaluates emerging technologies, and improves software quality, security, productivity, and operational efficiency.

Build AI-native products and ventures from zero to one in a fast-paced, in-person venture studio. Shape product strategy, validate user problems, make foundational architecture and tooling decisions, prototype and ship quickly, and collaborate closely with designers, researchers, strategists, and venture leaders. The role requires strong technical judgment, product thinking, comfort with ambiguity, emerging-technology awareness, and ownership of business and user outcomes.

Drive technical alliances with hyperscalers by developing reference architectures, technical content, and joint solutions. Influence product roadmap, enable sales through training and demos, support co-marketing, and represent Dynatrace in partner communities.

Lead enterprise architecture and engineering strategy for AI-native, cloud-native platforms. Define AI-enabled patterns, governance, and guardrails; drive platform modernization, CI/CD, IaC, automated testing, reuse-first engineering, and mentor architect-engineers while ensuring security, resiliency, and auditability.

Lead enterprise deployment, governance, and operations for Microsoft Copilot and Power Platform across M365. Manage tenant controls, licensing/credit governance, AI risk/compliance, Microsoft vendor relationships, SharePoint/OneDrive content readiness, and analytics/reporting. Partner with architects, Security, Legal, Procurement, and business stakeholders to ensure secure, compliant, and adopted AI platform operations.

Lead full-stack web development on GCP to build AI-powered search and discovery experiences. Design and implement web apps, services, and indexing pipelines, optimize performance, automate CI/CD and testing, mentor engineers, collaborate with product and ML partners, and productionize search/recommendation capabilities.

Lead a team building cloud-native, full-stack microservices and AI-enhanced risk management solutions. Design, deliver, and mentor on scalable AWS-based systems using modern web stacks and generative AI tooling to meet regulatory and business needs.

The Senior Backend Engineer will design, build, and scale AI-driven operations, manage the product lifecycle, and implement AI technologies while ensuring data security and system performance.

Build and maintain Palantir Foundry data pipelines, ontologies, applications, workflows, and decision-support capabilities for defense missions. Translate stakeholder needs into technical architectures, integrate structured and unstructured data, troubleshoot production systems, and support client deployments. Collaborate with engineers, analysts, product owners, and mission stakeholders while applying testing, version control, documentation, and deployment best practices. The role requires client-site travel and eligibility for a Secret clearance.

Owns the technical design, development, maintenance, and operations of software products for CMS’s QMARS healthcare systems. Researches technologies, develops proofs of concept, mentors engineers, enforces team processes, and contributes to modernization using Python, React or Angular, TypeScript, and AI technologies. The role requires prior supervisory or lead experience and supports a remote-first team serving public health and healthcare quality improvement programs.

Leads a diverse software engineering team developing complex system software and tools. Manages headcount, budgets, schedules, project delivery, vendor partnerships, risks, and process improvements. Collaborates with technical, program, executive, and AI teams to integrate AI innovations into products and processes. Oversees hiring, coaching, performance management, and career development while providing technical guidance and ensuring high-quality, on-time execution aligned with organizational roadmaps.

Lead the technical architecture for post-sales Customer Success, Renewals, Professional Services, Support, and GTM Operations. Build automation, AI capabilities, integrations, workflows, customer intelligence, and shared data models that improve retention, renewals, efficiency, and customer engagement. Establish engineering standards and technical direction across GTM systems while partnering with business leaders, engineers, and the Pre-Sales GTM Engineer.

Build and maintain the TypeScript-based Duo Client SDK, including Node.js core packages, public APIs, browser-compatible modules, Vue 3 client components, and platform adapters. Responsibilities include migrating consumers from the GitLab Language Server, managing versioning and deprecation paths, strengthening credential security, optimizing browser performance, writing tests, conducting code reviews, and participating in on-call support.

As a Staff Software Engineer, you'll design, build, and test Gusto's core platform services, mentor engineers, and collaborate with various teams to solve complex engineering problems.

Lead design and delivery of enterprise integrations, automation, and AI-driven workflows across SaaS platforms. Architect scalable APIs, middleware, and conversational self-service experiences; partner with Security, Infrastructure, and Product; mentor engineers and drive long-term platform strategy, governance, and operational excellence.

Design and build end-to-end software primitives for AI infrastructure: domain modeling of power/datacenters/chips, authorization, audit, orchestration, vendor data ingestion (KMZ/BIM/Revit), and agent integration to enable safe, auditable agent operators. Ship production-quality systems and work across ambiguity to turn unstructured data into durable, composable entities.

Own the full product loop: identify high-impact problems, rapidly prototype and ship AI-accelerated solutions, build internal tools and automations, collaborate with operations and business teams, and iterate based on usage and data to drive adoption and business impact.

Develops secure, scalable full-stack applications for Asset Management. Responsibilities include software design, coding, testing, troubleshooting, architecture, data analysis, visualization, and operational stability. Uses enterprise-authorized AI coding tools responsibly to improve development productivity while validating outputs for security and correctness. Builds services with Hibernate, Spring JPA, PostgreSQL, REST APIs, and GraphQL, with preferred experience in Kafka, Avro, React, and AWS.

Leads full-stack software engineering within an agile Asset Management team. Develops, reviews, tests, debugs, and operationalizes secure production code using Java, Python, AWS, Spring JPA, Hibernate, PostgreSQL, REST, and GraphQL. Drives adoption and governance of AI-assisted engineering practices, validates AI outputs, mentors technical teams, influences architecture and product decisions, and promotes SDLC automation, reusable frameworks, scalability, resiliency, and security.

Design, develop, test, deploy, and support Genesys IVR, voice, chat, and conversational AI solutions in a cloud contact-center environment. Partner with business and technology teams to translate requirements into technical solutions, improve customer self-service, and deliver AI-powered virtual assistants and automation. The role also involves SQL-based data analysis, reporting, data quality validation, troubleshooting, and AI-assisted UX/UI prototyping and front-end development.

Develop production-quality full-stack applications using Angular, TypeScript, Java, and Spring Boot. Support AI-assisted software delivery, application modernization, data modeling, testing, debugging, documentation, and enterprise product development. Collaborate in sprint-based teams to build user-facing features, validate data, improve application performance and reliability, and create reusable AI development practices.