Top Software Engineer Jobs

Own the implementation, hardening, and polish of game AI behaviors and systems for shipping. Collaborate with design, animation, and other disciplines to tune AI features and support the creative vision. Ensure reliable, stable enemy behaviors and enhance existing architecture. The role requires deep Unreal Engine and modern game AI experience, strong C++ skills, animation systems knowledge, and at least one shipped game title focused primarily on AI.

Leads design, development, testing, deployment, and production support for secure Java microservices and REST or event-driven APIs. Owns DevOps execution, CI/CD pipelines, automated quality gates, resilience, observability, and comprehensive testing. Promotes responsible AI-assisted engineering practices, evaluates technology vendors, and guides teams on scalable AWS or private-cloud solutions using Cassandra and Kafka.

Own end-to-end enterprise platform deployments, from scoping customer workflows through production launches and iteration. Configure AI agent behavior, integrations, retrieval, prompts, workflows, operating procedures, and safety guardrails within complex SAP environments. Create technical artifacts, evaluation plans, and customer documentation; apply AI tools to development, testing, data, and support. Partner with the Platform team to develop repeatable deployment abstractions while working directly with enterprise stakeholders.

Leads digital applications engineering strategy, software development, engineering team management, Level 3 support, budgets, vendors, and offshore resources. Oversees ecommerce, mobile, MarTech, AdTech, personalization, loyalty, customer data, and media monetization platforms. Drives architecture reviews, technical debt reduction, cross-product integrations, process improvement, hiring, performance management, and technology solutions that improve productivity and profitability.

Leads the design and implementation of large-scale, cloud-native full-stack systems for cloud operations resilience. Develops distributed microservices using Python, Go, JavaScript, TypeScript, AWS, Docker, and Kubernetes. Defines platform roadmaps, architecture, engineering standards, and operational practices while improving reliability, performance, and technical debt. Mentors engineers, leads design reviews and cross-functional initiatives, evaluates emerging AI technologies, and influences enterprise technology strategy.

Build and lead development of cloud-based, full-stack systems supporting observability, connectivity, resilience, and availability. Design distributed microservices, define service boundaries, establish engineering standards, improve system performance, reduce technical debt, and implement AI-powered solutions. Collaborate with product managers and architects, influence technology strategy, mentor engineers, and drive cross-functional technical initiatives using Python, Go, JavaScript, TypeScript, AWS, Docker, and Kubernetes.

Leads multiple software engineering teams within employee platforms, providing technical guidance, managing delivery, coaching engineers, and ensuring compliance with business requirements and service levels. Drives responsible adoption of enterprise-authorized AI-assisted development, SDLC automation, and reusable engineering practices. Oversees stakeholder relationships, project dependencies, agile delivery, security, application resiliency, and cloud-native engineering initiatives.

Leads diverse technology projects and developer teams building cloud-based, full-stack risk management solutions. Provides technical direction across Agile teams, defines architecture and service integrations, mentors engineers, establishes engineering standards, and drives system performance and technical debt reduction. Develops distributed microservices and APIs using modern programming languages, databases, containers, AWS services, AI tools, CI/CD, and observability practices.

Design, build, test, deploy, and operate platform features for engineering teams. Develop AI-assisted workflows, distributed systems, observability, automated validation, progressive rollout, and recovery tools. Collaborate with partner teams, gather requirements, troubleshoot production issues, participate in reviews, and support features through their lifecycle, including on-call responsibilities.

Designs, develops, tests, deploys, and maintains Microsoft Power Platform applications, automations, virtual agents, and Power BI reports. Partners with business analysts and stakeholders to identify process improvements, digitize workflows, automate administrative tasks, and analyze data. Documents technical designs, supports governance and best practices, troubleshoots deployed solutions, collaborates on QA, estimates project effort, and mentors colleagues. The role requires onsite work in Kansas City and familiarity with programming, APIs, networks, SFTP, and machine learning concepts.

Develops and delivers interactive technical demonstrations showcasing Intel platforms, software, cloud, AI, networking, edge, and accelerated computing solutions. Responsibilities include demo research, solution design, software preparation, optimization, configuration, debugging, troubleshooting, stakeholder coordination, executive presentations, partner engagement, and event support. The role works in Intel labs, supports robotics and physical AI demonstrations, and requires 35% travel.

Develops, tests, deploys, and operates Azure Data product features in highly secured, air-gapped environments. Responsibilities include coding, architecture collaboration, automated testing, incident response, deployment automation, security hardening, telemetry, reliability improvements, and on-call support. The engineer works with partner teams to meet performance, scalability, privacy, compliance, and government customer requirements while using AI tools throughout the software development lifecycle.

Leads geographically distributed Business Analyst and Software Engineering teams delivering global enterprise Time and Pay solutions. Owns strategy, architecture, development, integrations, modernization, automation, quality, and operational performance across Oracle and ADP platforms. Partners with HR, Finance, vendors, and technology leaders to define roadmaps, address multinational payroll and workforce requirements, and deliver scalable solutions. Requires extensive enterprise application leadership, cloud, AI, systems integration, and transformation experience.

Design and build scalable Go or Rust backend services and data pipelines for asset discovery, recognition, and enrichment. Solve distributed-systems challenges involving concurrency, fault tolerance, and high-throughput processing. Integrate AI and ML capabilities, use AI-assisted development tools, contribute to architecture and technical standards, mentor engineers, and participate in code reviews and continuous improvement.

Leads enterprise technology development across ServiceNow, Salesforce, AI platforms, and integrated applications. Responsibilities include developing applications, implementing AI and automation, managing cross-platform projects, creating technology roadmaps, coordinating resources, supporting migrations, strengthening security and compliance, mentoring teams, and managing stakeholders. The role requires federal IT governance experience, enterprise-scale implementations, and the ability to obtain a Public Trust.

Leads Magna’s software engineering organization across multiple products and business lines. Oversees engineering managers, QA, DevOps/SRE, and architecture leaders while owning organizational development, delivery execution, modernization, quality, security, and operational reliability. Partners with executives and cross-functional teams to translate priorities into roadmaps and measurable outcomes. Guides AI-enabled product development, including responsible deployment of large-language-model capabilities, and supports integration of acquired platforms. This remote U.S. role requires approximately 10% travel to Philadelphia-area offices.

Designs and delivers secure, portable AWS edge-computing solutions for tactical and disconnected environments. Responsibilities include deploying AI/ML models to edge devices, using AWS IoT Greengrass, Snowball Edge, SageMaker, containers, microservices, and GitLab CI/CD. The role emphasizes zero-trust security, optimized model deployment, resilient connectivity, secure updates, and collaboration on complex software solutions. A Secret clearance must be obtainable; Top Secret clearance and AWS certification are preferred.

Leads hands-on development and architectural design of scalable, secure middleware platforms. The role establishes engineering standards, mentors engineers, applies DevSecOps and SRE practices, advises business and product stakeholders, and drives delivery of complex software solutions. Responsibilities include building Java and Spring Boot systems using Kafka, microservices, GraphQL, and NoSQL technologies; improving resilience and operational excellence; evaluating emerging technologies; and ensuring high-quality design, code, security, and technical documentation.

Design, prototype, develop, document, test, and debug software solutions for semiconductor equipment components and devices. Troubleshoot software issues, communicate with internal customers to understand requirements, and contribute to innovative software solutions involving machine learning and AI. This full-time role begins in Summer 2027 and includes approximately 10% travel.

Leads multiple .NET development teams and QA functions delivering secure, scalable Azure-hosted applications. Establishes Agile delivery practices, engineering metrics, testing standards, CI/CD and DevSecOps processes, application security controls, and production support practices. Drives adoption of AI-assisted development tools and leads AI-driven and agentic solution delivery. Partners with architecture, security, cloud, product, and business stakeholders while managing hiring, coaching, technical debt, compliance, and continuous improvement.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Leads full-stack software engineering teams and a portfolio of technology projects focused on developer experience, distributed systems, microservices, and cloud-native platforms. Sets technical strategy, oversees large-scale system design and delivery, manages engineering leaders, develops talent and succession plans, and aligns roadmaps with enterprise goals. The role involves Java, Python, cloud platforms, databases, containers, APIs, Agile delivery, and emerging AI technologies.

Leads engineering projects and developers building cloud-based, AI-powered risk management solutions. Designs distributed microservices and full-stack systems, establishes technical standards, partners with architects and product managers, improves system performance, reduces technical debt, and mentors engineers. The role uses AWS technologies, modern programming languages, databases, APIs, CI/CD, infrastructure as code, automated testing, and observability within Agile teams.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Design, develop, and operate scalable software platforms and automation for Azure network qualification infrastructure. Build tools for device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Develop AI-powered agents for troubleshooting, root-cause analysis, and engineering productivity. Create reliable distributed systems with observability, diagnostics, automated recovery, and scalability while collaborating across software and network engineering teams.