Top Software Engineer Jobs

Summer IT internship providing hands-on assignments across application/automation development, AI, cloud, data & analytics, security, networking and telecommunications. Interns receive mentorship, networking opportunities, and deliver a capstone presentation. Typical internships last 10–12 weeks in Bartlesville, OK or Houston, TX.

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 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.

As a Software Engineer Lead, you will design and develop AI solutions, lead tech teams, and ensure high-quality NLP capabilities. You'll integrate AI services into enterprise platforms and guide best coding practices.

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.

Tenure-track Assistant Professor to teach and advise undergraduate and graduate courses across computer information science, data science, and AI fields; engage in research, curriculum design, student mentorship, committee service, and pursue funding. Expected to deliver face-to-face, hybrid, and online instruction, support student recruitment and retention, and use active, project-based pedagogies.

The Head of Application Development leads software engineering and application development across all business areas. Responsibilities include strategic planning, team development, performance management, ensuring delivery of quality software, and managing relationships with stakeholders and vendors.

Lead company-wide AI adoption and build an embedded engineering and product organization to ship AI-native internal tools. Own enterprise systems (CRM, ERP, HRIS, OMS, WMS), IT operations, security, data governance, and M&A systems integration. Partner with product and data leadership, set architecture and roadmap, and build a leadership team for IT, security, and internal systems to drive measurable efficiency and adoption across Finance, Revenue, People, Legal, Support, and Operations.

Lead and grow a team building DPU-enabled, high-performance AI cloud infrastructure. Drive architecture, prototypes, production readiness, observability, security, lifecycle management, and cross-team delivery while hiring and mentoring engineers and ensuring operational reliability.

Design, develop, and deploy web and cloud applications using .NET, C#, Azure, Angular, React, and related technologies. Collaborate with clients to gather requirements, define goals, and recommend solutions. Participate in Agile/Scrum planning, code reviews, mentoring, testing, and DevOps practices. Explore AI-assisted development tools and help establish effective AI workflows. The role involves continuous learning, client engagement, and delivery of enterprise software and AI automation solutions.

Build and maintain end-to-end full-stack features across React and backend services using Elixir, Python, Go, and related technologies. Partner with product and design, own projects from specification through launch, apply testing and delivery best practices, shape architecture, resolve technical issues, and mentor junior engineers. The AI agents team develops systems enabling AI agents to reason, act, and improve customer experiences.

Build and operate end-to-end full-stack applications for transaction monitoring and data controls. Develop responsive UI components, Java Spring Boot microservices, REST APIs, event-driven Kafka and Spark pipelines, and cloud-native GCP solutions. Contribute to LLM, Agentic AI, and RAG automation initiatives while ensuring scalability, resilience, observability, security, and performance. Collaborate with cloud, security, data, risk, and compliance teams across globally distributed environments.

Lead architecture, bring-up, validation, optimization, and deployment of networking infrastructure for large-scale AI training and inference. Define networking requirements, design Layer 3/4 and RDMA/AI fabric solutions, develop validation and observability tooling, perform packet-level debugging and root-cause analysis, and collaborate across silicon, firmware, software, and Azure teams to ensure performance, scalability, and reliability of hyperscale AI clusters.

As a Founding AI Backend Engineer at Pakket, you'll enhance backend systems, debug the CV pipeline, and deploy services across warehouses, ensuring operational reliability and rapid feature deployment.

Lead developer enablement for firmwide developer tools: run demos, workshops, and office hours; create reusable examples and guidance; drive responsible adoption of AI coding tools; gather feedback for platform/product teams; advocate for developers across risk, tooling, and leadership; and help shape adoption strategy and enablement content.

Lead backend development and architecture in Laravel/PHP while embedding AI as a core system layer. Build AI agents, prompt pipelines, vector search, and automated workflows integrating third-party services. Optimize APIs, databases, and scalable, secure systems. Mentor engineers and collaborate with product and data teams to deliver reliable AI-powered features.

Lead AI software resiliency development, implementing features for reliability and fault tolerance in large-scale AI supercomputers, requiring hands-on coding and collaboration.

Design, integrate, validate, and optimize large-scale AI networking infrastructure. Lead Layer 3/4 and RDMA-based fabric architecture, performance characterization, congestion management, packet-level debugging, telemetry, automation, and deployment for hyperscale AI training and inference clusters.

Lead the design and delivery of AI solutions for legal professionals. Mentor engineers, establish AI engineering practices, and ensure scalable architecture and quality across systems.

Build and maintain developer workflows, CI/CD and deployment automation, containerized development environments, SDK packaging and release pipelines, AI performance dashboards, and productivity tools. Design scalable software and developer tools for novel hardware platforms, collaborate with hardware and ML teams, manage C++ codebases, establish engineering standards, and optimize software delivery and production readiness.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Design, develop, and maintain full-stack applications; lead technical discussions, mentor junior members, and improve products and technologies.

The Senior Innovation Engineer develops and implements Pega intelligent automation solutions, collaborating with architects and teams to enhance digital transformation projects.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

Lead engineering execution and people management for an open-source enterprise AI product transitioning from R&D incubation to production. Manage a senior engineering team, contribute code, review technical work, improve planning and release practices, and ensure quality, reliability, security, privacy, and maintainability. Partner with product and technical leaders on AI-enabled, multi-platform, customer-controlled architectures, while supporting hiring and scaling the team for enterprise adoption.