Top Software Engineer Jobs

Design, code, test, and maintain applications using Kotlin, Rust, and SwiftUI. Implement ATDD and CI/CD, build API integrations and microservices, manage application lifecycle and project planning, conduct code reviews and debugging, collaborate with clients, and apply analytical thinking for business process improvements.

Leads software engineering projects and developer teams building distributed microservices and full-stack systems. Develops cloud-based solutions using Java, Python, databases, Docker, Kubernetes, and AWS technologies. Collaborates with product managers, mentors engineers, evaluates emerging technologies, and delivers enterprise platforms supporting regulatory and customer needs.

Build and deploy quantitative risk models, pricing libraries, margin replication tools, and real-time monitoring systems for futures markets. Integrate AI and machine learning for predictive risk modeling, anomaly detection, and trading surveillance. Support live trading, investigate incidents, analyze market behavior, and implement systemic fixes. Collaborate with traders and engineering teams, guide risk-tech architecture, and mentor junior staff. Coverage during Asian market hours may include early mornings or overnight shifts.

Leads multiple engineering teams and managers, defining technical strategy, improving stability and quality, and ensuring predictable delivery. Partners with Product, Architecture, business stakeholders, and external partners to prioritize solutions, manage technical debt, and support organizational growth. Develops engineering talent and standards while advancing cloud, DevOps, event-driven architecture, reliability, security, and AI-driven automation initiatives.

Build and maintain Layla’s cross-platform Flutter mobile applications for iOS and Android. Own end-to-end feature delivery, including architecture, API integration, data modeling, testing, performance, reliability, and release support. Collaborate with product, design, and backend teams to create accessible conversational travel-planning and booking experiences. Integrate AI/ML capabilities responsibly, contribute to native platform interoperability, improve engineering architecture and standards, and mentor other engineers.

Build and maintain Layla’s cross-platform Flutter mobile applications for iOS and Android. Own features end to end, including design, API integration, data modeling, testing, release, and support. Collaborate with product, design, and backend teams to create accessible, performant travel-planning and booking experiences. Integrate AI-driven capabilities responsibly, improve mobile architecture and reliability, contribute to native interoperability, and mentor engineers.

Build fast, accessible, component-based web interfaces for Layla’s conversational AI travel-planning and booking experience. Translate designs into maintainable React applications, collaborate across Product, Design, and backend teams, integrate AI/ML capabilities responsibly, optimize performance and reliability, run experiments, influence frontend architecture, and mentor engineers through reviews and knowledge sharing.

Build fast, accessible, component-based web experiences for Layla’s AI-powered travel planning and booking platform. Translate designs into maintainable frontend code, integrate AI/ML capabilities, improve performance and reliability, run product experiments, and collaborate across Product, Design, and backend engineering. Contribute to frontend architecture, accessibility, quality, and reusable patterns while mentoring engineers through reviews and knowledge sharing.

Design, build, test, and launch reliable, scalable business insurance products and AI-powered customer experiences. Partner with product, design, and cross-functional teams to iterate using feedback and metrics. Lead multi-quarter projects from scoping through delivery, communicate technical tradeoffs, and mentor engineers through pairing, code review, and knowledge sharing.

Designs, builds, and operates secure, scalable cloud and GPU infrastructure platforms for enterprise AI/ML workloads. Leads architecture, production coding, Kubernetes and container operations, CI/CD, infrastructure automation, performance optimization, and reliability efforts. Partners with AI/ML and platform teams to support distributed multi-GPU training and inference. Provides technical leadership while advancing responsible AI-assisted engineering, secure SDLC practices, automation, and operational excellence.

Architect and build high-performance distributed infrastructure for batch and streaming data across global regions. Optimize state management, checkpointing, JVM performance, and exactly-once processing. Develop AI infrastructure including vector indexing, agentic workflows, and real-time data streaming. Own the full software development lifecycle, contribute to shared tooling and SDKs, and mentor engineers through technical leadership and design reviews.

Lead architecture and development of GM’s in-vehicle AI assistant platform on Android Automotive OS. Build scalable APIs, SDKs, edge-cloud integrations, CI and automated validation infrastructure, and robust AIDL/IPC application contracts. Guide engineering execution, optimize latency and memory, integrate AI/ML evaluation pipelines, and collaborate with product and UX teams. The role requires extensive Android architecture experience, technical leadership, Kotlin and Java expertise, and familiarity with distributed client-server systems.

Build and operate secure, scalable AI compute platform services, including backend APIs, asynchronous workflows, Kubernetes controllers, and multi-tenant workload capabilities. The role focuses on distributed training and inference, platform reliability, observability, developer tooling, and infrastructure simplification. Responsibilities include collaborating across engineering teams, improving scalability and developer productivity, and providing technical leadership for production AI platform capabilities.

Design and build secure, scalable platform services for distributed AI training and inference. Develop backend APIs, Kubernetes controllers, orchestration systems, asynchronous workflows, multi-tenant access controls, and developer tools. Improve reliability, observability, scalability, and engineering productivity while partnering with infrastructure and AI teams. The role also provides technical leadership, mentoring, and cross-functional collaboration throughout platform development and production delivery.

Designs and develops highly available cloud services for AI inference workloads. Responsibilities include building Kubernetes controllers and platform capabilities for deployment, scheduling, scaling, recovery, upgrades, observability, and lifecycle management. The role leads production readiness reviews, resolves complex infrastructure issues, improves reliability and performance, drives architecture and design reviews, mentors engineers, and influences technical direction across teams.

Lead an agile engineering team to design, develop, test, and operate secure, scalable production software. Provide technical guidance, influence product and architecture decisions, deliver high-quality code, and promote firmwide engineering practices and modern cloud-native technologies.

Manages multiple IT and data engineering teams, overseeing staffing, performance, priorities, delivery, metrics, and stakeholder communication. Leads the design, development, and delivery of Databricks-based data platform components using Raw, Refined, and Presentation medallion architecture layers. Applies AI and machine learning within data engineering, ensures operational standards, coaches employees, and balances immediate delivery needs with long-term engineering objectives.

The Chief Technology Officer leads application development, data and analytics, quality assurance, technology vendors, technical strategy, budgets, and digital transformation. The role partners with executives and the Head of AI to deliver technology initiatives, adopt emerging technologies, maintain governance and SOX compliance, establish performance metrics, and develop technology talent. The CTO oversees teams and ensures projects support business objectives, customer experience, operational efficiency, and long-term organizational growth.

Develops end-to-end core-system features, including AI-enabled functionality, testing, backend architecture, production monitoring, customer escalation management, code reviews, and collaboration with product managers to translate business requirements into scalable technical solutions.

Leads software engineering and data technology teams, coaching them on Lean, Agile, DevSecOps, DataOps, MLOps, automation, security, data quality, and observability. Drives engineering maturity, continuous improvement, team formation, staffing, innovation, and delivery outcomes. Manages at least five technology professionals, including performance, hiring, development, compensation, and corrective actions. Partners with governance, architecture, analytics, and business stakeholders to deliver secure, trusted enterprise data platforms and solutions.

Design and implement intelligent automation for AV software development, testing, release, and operational workflows. Build CI/CD pipelines integrating simulation and hardware-in-loop testing, develop engineering data pipelines and metrics, and create AI-enabled tools for test analysis, failure classification, defect triage, reporting, and workflow orchestration. Establish evaluation, governance, security, and monitoring standards for AI solutions while improving release readiness, software quality, engineering productivity, and cross-functional visibility.

Develop backend services, APIs, automation tools, and CI/CD workflows for virtual ECUs, software-in-the-loop simulation, orchestration, and AI-enhanced validation. Integrate simulation and AI/ML components, optimize compute-intensive workloads, manage artifacts and metadata, and collaborate with DevOps and simulation teams. The role requires software development experience with embedded or simulation systems, cloud and distributed systems knowledge, CLI and MCP architectures, and database experience.

Lead and contribute to full-stack Java/React development, design secure high-quality production code, drive adoption of AI-assisted engineering, improve automation and operational stability, evaluate vendor architectures, and lead engineering communities of practice while promoting resilient, secure CI/CD practices.

Lead technical delivery for analytics-focused software: design, develop, test, and operate secure, high-quality production code. Drive automation and CI/CD, evaluate vendor/architecture choices, mentor junior engineers, and promote resilient cloud-native solutions within financial services technology teams.

Lead development of secure, high-quality production software for analytics and credit risk; design, code (Python/Java), review, troubleshoot, automate remediation, drive CI/CD and cloud-native solutions, mentor junior engineers, evaluate vendors, and promote new technologies.