Top Software Engineer Jobs

Lead and contribute to design, develop, and maintain scalable Java/Spring Boot services on AWS. Drive adoption of enterprise-authorized AI-assisted engineering practices, ensure operational stability and monitoring (Prometheus/Grafana), troubleshoot complex issues, participate in architecture and code review, automate remediation, and mentor/lead software engineers.

Lead and architect production-grade trading systems for Credit Pre-Trade Technology, build AI-native platforms, develop and maintain secure scalable code, partner with trading and product teams, drive AI-assisted engineering practices, support production stability and automation, and lead technical evaluations and communities of practice.

Develop and maintain end-to-end LiDAR and camera perception software for robotics platforms. Responsibilities include sensor drivers, ROS 2 packages, GPU-accelerated processing, calibration, synchronization, recording and playback tools, Docker environments, packaging, CI/CD, hardware-in-the-loop testing, and production release automation. The engineer will support integration issues and collaborate closely with hardware, silicon, algorithm, manufacturing, and customer teams.

You will lead the Mobile AI engineering team, defining roadmaps, improving product quality, and collaborating cross-functionally to deliver mobile AI solutions.

As a Graduate Engineer, you'll design and develop AI agents and features while learning finance operations, coding best practices, and developing APIs in a collaborative environment.

Develop AI agents for finance workflows, design APIs, enhance engineering practices, ensure data security, and facilitate user collaboration.

Lead technical strategy and architecture for CoreWeave's orchestration platform (SUNK). Own critical orchestration components, drive cross-org initiatives in scheduling, quota enforcement, and hyperscale scaling. Mentor senior engineers, establish reliability and observability best practices, and ensure workloads run reliably and efficiently for large GPU ML training and inference clusters.

Lead and scale engineering across application, backend, infrastructure, and data teams. Responsibilities include hiring and developing engineers, guiding architecture and system design, driving reliable product execution, establishing engineering standards, shaping platform strategy, and partnering with AI, product, and customer-facing teams. The role also requires maintaining strong reliability, security, and privacy practices for clinical patient data.

The role involves developing advanced computational methods for semiconductor manufacturing, leading innovation, and scaling software for high data processing needs.

Build and own AI-powered research-enablement tooling, shape the engineering roadmap, make architecture decisions, establish engineering processes, and help scale the team. The role partners closely with research, sourcing, engineering, and the CEO to improve report-production speed and product adoption. Responsibilities also include delivery planning, communicating risks, designing technical interviews, and developing external API or MCP capabilities.

Support development of web and mobile applications, APIs, automation tools, and AI/ML integrations. Write, test, review, and document maintainable code; troubleshoot issues; optimize performance in cloud environments; assist with model deployment and validation; and collaborate with hardware, firmware, and product teams under mentorship.

Develop, integrate, test, deploy, and maintain scalable end-to-end analytics applications for federal government customers. Collaborate with data scientists and mission analysts to build front-end and back-end tools, operationalize data science, and support analyst workflows. Work with customer architectures, data repositories, big data, machine learning, and application development processes, including requirements analysis, design, implementation, testing, integration, deployment, and maintenance.

Lead architecture and implementation of LangSmith platform features across Go, Python, and TypeScript. Collaborate with product, design, customers, and internal stakeholders to deliver scalable observability and evaluation capabilities. Write clean, tested code, design high-performance APIs, work with Postgres and Redis, and drive rapid project execution. The role requires strong fullstack engineering, communication, ownership, and customer engagement skills.

Lead and contribute to design, develop, test, and maintain secure, scalable Java-based enterprise applications. Drive architecture reviews, apply AI-assisted engineering practices, automate remediation, mentor teams, and promote reuse and operational stability across the SDLC.

Lead design, build, and operation of AI-powered Growth experiences (conversational onboarding and AI-driven email). Own technical strategy for an AI Voice Agent and ACE-powered email systems, design APIs and frontend/backends, partner cross-functionally, establish applied-AI engineering patterns, measure impact, and mentor engineers to improve product quality and responsible AI use.

Configure, integrate, and deploy the BT tool stack (Snowflake, Salesforce, Streamlit, workflow tools). Build integrations and Streamlit apps, deploy AI-enabled automations, maintain Snowflake data models and reports, catalog assets with DataHub, implement SDLC/testing/guardrails, ensure data security, and partner with Engineering/InfoSec while mentoring BT team members.

Own end-to-end features across Go backend services and React/TypeScript frontend applications. Design, develop, and debug high-load distributed systems, APIs, integrations, and event-driven services. Use AI coding agents as part of daily development, critically reviewing and verifying generated output. Contribute to architecture decisions, resolve complex production issues, and improve engineering practices for AI-assisted delivery.

Lead the consolidation of fragmented robotics services into a unified, scalable production platform. Establish architecture, version control, CI/CD, testing, OTA updates, observability, reliability practices, and customer-system integrations. Own production uptime and incident response while mentoring engineers, defining engineering standards, and eventually leading the software team.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

The Staff Software Engineer will lead the architecture and design for AI workload orchestration on Kubernetes, mentoring engineers and driving technical initiatives across teams.

Lead design and delivery of enterprise integrations, automation, and AI-driven workflows across SaaS platforms. Architect scalable APIs, middleware, and conversational self-service; partner with Security, Infrastructure, and Product to reduce operational toil and enable reliable, extensible enterprise platform capabilities.

Design, build, test, deploy, and maintain cloud-based web applications and microservices. Ensure performance, reliability, and code quality while collaborating on new features, debugging, and optimizing systems. Use AI development tools daily, contribute to infrastructure as code, and promote maintainable architecture and documentation.

Lead and remain hands-on building an AI-first developer portal and secure external API platform. Define architecture for agent-ready workflows, authentication/credential flows, contract-first APIs, resiliency, observability, and AI-enabled support. Drive cross-functional delivery, coach engineers, and ensure operational controls, auditability, and production readiness for integrations.

Senior software systems engineer responsible for high-level design and oversight of software, hardware, and firmware systems. Lead Agile development, ensure quality and security standards, mentor engineers, manage multiple projects, support procurement, perform technical reviews, generate performance reports, and integrate emerging technologies into defense test and training environments.

Build and maintain backend services, APIs, and integration layers for a modular ecommerce platform. Integrate personalization, semantic and LLM search, DAM, PIM, SAP/HANA, ERP, analytics, and customer data systems. Use AI coding agents throughout development while validating code quality, security, performance, and reliability. Design scalable APIs, automated testing, observability, and reusable architecture while collaborating with internal teams, vendors, and implementation partners.