Top Software Engineer Jobs

Leads multiple software engineering departments and sets strategy for transactional data, analytics, and AI platforms. Directs agentic AI-enabled engineering and SDLC automation, establishes governance and security guardrails, and prepares data applications for AI agent consumption. Oversees large-scale distributed systems, cross-functional delivery, data quality, resilience, incident response, stakeholder alignment, and talent development across a global banking organization.

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.

Leads a team of software engineers in designing, developing, testing, and operating secure, resilient Java microservices. Oversees architecture, implementation, technical troubleshooting, and design documentation for event-driven systems using Kafka, Spring Boot, and cloud infrastructure. Promotes automation, responsible AI-assisted development, secure coding, continuous delivery, operational stability, and adoption of emerging technologies. Provides technical leadership across agile teams and evaluates architectural solutions with vendors and internal stakeholders.

Leads development of secure, scalable Java and AWS software systems, including microservices, event-driven platforms, and production machine-learning systems. Designs data and feature pipelines, model deployment and monitoring, automation, CI/CD, and operational stability practices. Guides code reviews, testing, secure coding, vendor evaluations, and responsible adoption of AI-assisted engineering tools. Collaborates across product, data, platform, SRE, and governance teams while promoting MLOps, LLM, observability, and model-monitoring practices.

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.

Build and lead production Python software for technology-risk oversight, including data pipelines, PostgreSQL systems, authenticated APIs, and LLM agent workflows. Develop RAG, tool orchestration, evaluation, and guardrails; ensure security, auditability, observability, testing, reliability, and responsible AI use. Collaborate with Product, Risk, Controls, Compliance, and data teams while delivering dashboards and evidence packages.

Lead a global agile scrum team to design, build, and operate scalable, secure microservice-based applications. Integrate AI (Claude Code) into development and delivery, drive architecture and technical decisions, mentor engineers, enforce AI-assisted engineering governance, and ensure production quality, stability, and automation across the SDLC.

Lead design, develop, and deploy secure, scalable full-stack applications (Java or Python) for finance planning and analysis. Drive architecture reviews, operational stability, CI/CD automation, cloud-native AWS deployments, and integration of AI/ML/LLM capabilities. Mentor teams and lead engineering communities of practice.

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 design, architecture, and delivery of full-stack, AI-enabled applications. Provide technical leadership across frontend, backend, APIs, databases, and AI integration. Drive engineering best practices, CI/CD, automated testing, cloud-native (AWS) solutions, and adoption of AI-assisted development while ensuring secure, resilient, scalable systems.

Leads enterprise UI/UX engineering and digital experience strategy, architecture, and delivery. Responsibilities include modernizing legacy applications with React and Angular, governing design systems, establishing front-end standards, ensuring accessibility and security compliance, and developing AI-powered experiences such as copilots, conversational interfaces, intelligent search, personalization, and workflow automation. The role partners across Product, Engineering, Security, Architecture, and business teams in financial services environments.

Provides hands-on technical leadership for full-stack AI-enabled enterprise applications. Designs Angular and TypeScript frontends, Java and Spring Boot backend services, REST APIs, and LLM integrations. Mentors developers, conducts code reviews, establishes engineering practices, resolves complex technical issues, and partners with architects, product owners, business stakeholders, and AI/ML teams. The hybrid Tucson role requires onsite work one to three times monthly, including occasional factory or classified-environment work.

Develop and maintain full-stack Java applications using Java EE, RESTful microservices, Angular, TypeScript, Node.js, SQL, PL/SQL, and Oracle. Use AI coding assistants such as GitHub Copilot for code generation, debugging, optimization, and prompt-driven development. Validate AI-generated code for accuracy, performance, and security while applying JVM performance profiling. Collaborate on production-ready solutions, with familiarity in CI/CD, DevOps, Unix scripting, Docker, caching, and SAML preferred.

Develop and deliver native iOS features for MyFitnessPal’s AI-powered food logging experience. Responsibilities include implementing user interfaces, optimizing performance and network communications, building tested and secure solutions, collaborating with product and design teams, researching technical approaches, mentoring developers, and contributing to deployment and engineering best practices.

Develop and ship software end to end using AI-assisted coding tools, while reviewing, testing, securing, and correcting generated code. Lead modernization work, evaluate AI tooling through measurable outcomes, establish guardrails, and share effective practices with engineering colleagues. The role requires strong software fundamentals, experience across legacy and modern stacks, production ownership, and independent judgment in ambiguous situations.

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.

Own and operate the Apigee X API gateway, including proxies, shared flows, security policies, environments, deployments, governance, CI/CD, monitoring, and incident response. Partner with infrastructure, network, security, and engineering teams to establish API standards and onboard users. Extend the gateway for LLM traffic and MCP integrations with provider abstraction, authentication, rate limiting, logging, AI safety controls, and auditability in a regulated banking environment.

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.

Build and maintain full-stack internal network automation and AI-Ops products, including operational dashboards, topology visualizations, real-time data views, conversational AI interfaces, APIs, and data integrations. Integrate AI services, network and inventory platforms, and vendor tools. Use TypeScript, Python, CI/CD, testing, and cloud technologies while translating operational requirements into technical solutions and supporting globally distributed Agile teams.

Develop and integrate networking software for NVIDIA BlueField and ConnectX platforms supporting large-scale AI infrastructure. Work with customers and internal teams on RDMA and RoCE solutions, troubleshooting issues across applications, libraries, drivers, firmware, and switches. Analyze performance metrics, create automation and test cases, validate fixes, and support deployments from testing through production while documenting technical findings and decisions.

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.