Top Software Engineer Jobs

Build and operate a high-performance AI Gateway that securely routes, inspects, and governs enterprise traffic to LLM providers. Develop asynchronous Python and FastAPI services, streaming APIs, network protocols, cloud-native infrastructure, messaging systems, security integrations, observability, and CI/CD pipelines. The role involves Kubernetes deployments, scalable concurrent connections, identity and access management, AI/LLM workflows, cost optimization, and incident response. Korean-English bilingual ability is highly preferred.

Build and scale customer-facing Android marketplace applications using Kotlin, Compose, and modern Android architecture. Own complex features end to end, lead technical direction, improve testing and CI/CD, support releases and observability, and modernize legacy codebases. Use AI tools for coding, testing, debugging, documentation, and operational efficiency while mentoring engineers and collaborating with product, design, backend, platform, QA, and iOS teams.

Lead the architecture and implementation of Docker’s AI Gateway, including model and tool routing, MCP, control-plane systems, credential vaulting, policy enforcement, observability, analytics, caching, and rate limiting. Solve complex distributed-systems problems, establish technical direction, improve infrastructure, mentor engineers, and shape product strategy. Build secure, scalable services supporting model orchestration, agent evaluation, replay, and enterprise-grade governance.

Architects modular, multi-tenant SaaS platforms and AI-driven engineering workflows. Owns service boundaries, module contracts, identity, security, cloud infrastructure, migrations, observability, and agent guardrails. Designs AI product features, selects model providers, establishes evaluation and cost controls, and reviews high-risk changes. Coaches developers on specification writing and agent orchestration while collaborating with product and engineering leadership.

Leads software development and platform support across front-end, back-end, data, and enterprise applications. Designs, deploys, tests, secures, and improves systems while driving data architecture, automation, ITIL processes, documentation, and operational compliance. Partners with business and technology stakeholders to define data needs, improve user experience, manage cross-team initiatives, and deliver agile solutions. Provides technical guidance, evaluates vulnerabilities, supports AI-enabled engineering practices, and mentors less experienced team members.

Build and support reliable dashboards for AI infrastructure and financial models, including TCO, tokenomics, and compute capital models. Responsibilities include implementing features, loading model releases, validating data, developing accuracy checks, collaborating with analysts, creating charts and explanations, answering client questions, and contributing to research newsletters. The role requires strong Python or TypeScript skills, software engineering experience, numerical accuracy, and effective use of AI coding agents.

Lead engineering teams and technology portfolios while designing and implementing large-scale, distributed, cloud-native systems. Build full-stack solutions using modern programming languages, microservices, databases, containers, and cloud platforms. Provide technical leadership on architecture, platform roadmaps, reliability, observability, coding standards, and enterprise technology strategy. Mentor engineers, collaborate with product and architecture leaders, and drive cross-functional technical initiatives supporting regulatory and customer needs.

Develop and support full-stack applications across web, iOS, Android, and Linux platforms. Build real-time mapping and image-processing solutions, implement front-end components, REST back-end services, and database schemas, and maintain third-party dependencies. Collaborate with product and engineering teams in an Agile environment to deliver reliable software milestones. The role also provides technical support for field applications and requires occasional travel to field offices and testing areas.

Develop Unix applications and complex CNO capabilities using C, C++, Rust, or Python. Collaborate with AI/ML and software engineers to build systems supporting national security operations, define operational parameters, and apply software lifecycle practices across design, development, testing, validation, and deployment. The role also involves embedded software validation and leveraging AI-assisted development.

Develop Windows applications and complex software for national security and computer network operations. Collaborate with AI/ML and software engineering teams, apply network operations expertise, manage software lifecycle activities, and design, test, validate, and deploy Windows-focused solutions. The role requires object-oriented programming experience, strong C/C++/C# skills, familiarity with Rust or Python, and a TS/SCI clearance with polygraph.

Lead a product-focused engineering team building WorkOS Dashboard features for onboarding, growth, billing, monetization, and AI assistance. Responsibilities include technical strategy, architecture, prototyping, product decision-making, customer discovery, roadmap development, hiring, mentoring, and team growth. The role partners closely with product, design, finance, go-to-market, recruiting, and engineering teams while balancing rapid delivery with reliability, billing correctness, and AI quality.

Leads the global Shop Floor Control and MES engineering organization across wafer fabs. Defines the technology strategy and roadmap, oversees delivery, modernizes legacy platforms, and partners with manufacturing and automation teams. Provides technical direction for production execution, lot tracking, equipment integration, WIP management, data collection, and factory event processing. Builds organizational capability through hiring, coaching, and succession planning while ensuring scalable, resilient, secure, and standardized manufacturing systems.

Participate in a 12-week primarily remote technical internship, contributing to projects in software engineering, AI/ML, cloud and DevOps, cybersecurity, data, or research. Interns collaborate with technical teams, participate in Agile ceremonies, receive mentorship, develop and document solutions, communicate progress, and present a final capstone project. Attendance at a required onsite summit in Bridgeport, West Virginia is included.

Manages secure desktop and web application integrations, automation, APIs, and vendor-supported systems. Designs, develops, tests, documents, upgrades, and troubleshoots integrations while supporting application security assessments, vulnerability resolution, and compliance. Collaborates with business teams to translate processes into technology requirements, evaluates new applications, writes maintainable code, and provides technical support. Preferred experience includes PowerShell automation, API development tools, AI and bot development, cloud SaaS, and complex SQL.

Deploy Nexus enterprise AI software for customers, from technical discovery through production validation and handoff. Build integrations, Python and SQL transformations, notebooks, APIs, and automation; validate data pipelines and semantic models; resolve technical issues; document and stabilize deployments; communicate with customer stakeholders; and convert recurring deployment challenges into reusable engineering improvements.

Build and productionize data and AI applications on Palantir Foundry for biomedical domain teams. Responsibilities include designing data pipelines, transformations, ontology models, workflow applications, integrations, access controls, data quality checks, and production monitoring. The role leads discovery and iterative delivery, partners with product, data, governance, and platform teams, supports user adoption, and creates reusable delivery patterns. Candidates need strong programming, data and application engineering, stakeholder management, and biomedical domain experience.

Leads the technical strategy and hands-on engineering for Capital One’s customer management platforms. Responsibilities include modernizing legacy systems into microservices and event-driven architectures, setting platform and API standards, building full-stack solutions, establishing SRE and engineering productivity functions, enabling experimentation and AI-powered product delivery, and mentoring senior technical leaders. The role leads more than 100 engineers while contributing directly to architecture, coding, system optimization, and operational excellence.

Designs scalable systems, leads end-to-end technical execution, drives cross-team initiatives, and contributes hands-on production code. The role maintains engineering standards across architecture, testing, CI/CD, observability, and DevOps; leads incident response and root-cause analysis; mentors engineers; troubleshoots production issues; and aligns technical delivery with product priorities.

Leads distributed, cross-regional software engineering teams responsible for Conference Tech platform integrations. Drives the integration roadmap, cloud architecture, API-centric and event-driven platform development, engineering excellence, SDLC rigor, quality, responsible AI adoption, and organizational change. Partners with business and IT leaders to deliver secure, scalable enterprise solutions aligned with strategic priorities and improved conference attendee experiences.

Leads engineering managers, software engineers, architects, data engineers, and support teams responsible for enterprise fraud technology platforms. Oversees real-time fraud detection, transaction monitoring, risk scoring, identity and payments fraud controls, case management, and 24x7 operations. Sets technology strategy, budgets, governance, SLAs, security, resiliency, and modernization standards. Drives cloud-native architecture, CI/CD, Infrastructure as Code, SRE, observability, event-driven systems, and real-time analytics while partnering with risk, cybersecurity, compliance, fraud operations, and business leaders.

Leads engineering strategy, teams, budgets, modernization, and operational accountability for enterprise AML technology platforms. Oversees transaction monitoring, risk scoring, investigations, case management, regulatory reporting, and financial crime detection capabilities. Drives cloud modernization, resiliency, security, CI/CD, Infrastructure as Code, SRE, observability, advanced analytics, machine learning, and graph analytics. Partners with AML Operations, Compliance, Risk, Cybersecurity, Audit, and business leaders while managing vendors, governance, controls, talent development, and platform performance.

Develops, tests, and optimizes signal-processing and physiological measurement algorithms for medical devices. Analyzes clinical and physiological datasets, performs modeling and experimentation, and supports algorithm development from feasibility through validation and product integration. Collaborates with software, hardware, systems, clinical, and quality engineering teams, and contributes to clinical data collection and human-subject study analysis.

Develop and maintain GUIs, dashboards, AWS applications, automated workflows, and AI/ML integrations. Responsibilities include coding, testing, debugging, software integration, requirements analysis, database querying, documentation, and process improvement. The role requires collaboration throughout the software development lifecycle and a current active TS/SCI clearance with a Maryland polygraph.

Lead a small engineering team while remaining hands-on in production coding. Deliver scalable product features, make architecture decisions with the CTO, apply AI-assisted development workflows, mentor engineers, and contribute to machine learning and product roadmaps. The role requires full-stack expertise with backend strength, applied machine learning knowledge, startup or core product ownership, and on-site work in New York City.

Develops and maintains database systems, analytical tools, data visualizations, reporting processes, and data governance practices for pavement research. Collaborates with research staff to improve data collection, processing, analysis, and presentation. Integrates artificial intelligence into analytical workflows, supports automated reporting, documents software and data workflows, and implements new technologies and infrastructure for continuous improvement.