Top Software Engineer Jobs

Leads development of full-stack, cloud-native software using Java, Python, AWS, microservices, APIs, and PostgreSQL. Designs scalable and secure systems, builds LLM and generative AI capabilities, and integrates AI agents into engineering workflows. Improves operational stability through automation and observability while contributing to Agile delivery, system architecture, and technical standards. Collaborates across initiatives and promotes responsible, secure validation of AI-assisted development outputs.

Improves the reliability, scalability, and observability of AI development and deployment platforms. Develops automation, CI/CD and GitOps workflows, dashboards, alerts, tests, and release validation processes. Investigates incidents, reduces operational toil, supports Kubernetes-based infrastructure, and collaborates across engineering teams on platform health. The role also includes autonomous-system integration, verification, validation, testing, and hardware/software interface troubleshooting.

Build and maintain end-to-end applications using React, Golang, and Node.js. Leverage AI development tools to improve speed and quality, collaborate with product and design, contribute to deployment and DevOps, and own features from concept through release. The role requires proactive problem-solving, rapid learning, scalable system design, and a strong builder’s mindset in a fast-paced energy and logistics technology environment.

Develops secure, scalable software solutions for JPMorganChase’s CX Loyalty Travel team. Responsibilities include application design, coding, testing, troubleshooting, architecture documentation, data analysis, system stability, and participation in agile engineering practices. The role uses .NET, C#, RESTful APIs, SQL, React or Angular, cloud technologies, and enterprise-authorized AI coding tools to deliver high-quality production systems.

Build and maintain Life360’s iOS advertising SDK, mediation and header-bidding integrations, ad formats, privacy and consent flows, instrumentation, and experimentation systems. Improve ad quality, performance, and reliability at large scale while collaborating with ad operations, data, product, and external partners. Use AI-native workflows with agentic coding tools, contribute to architecture and incident response, and mentor teammates.

Leads full-stack software engineering teams, technology portfolios, and large-scale cloud-native initiatives. Responsibilities include setting technical strategy, managing engineering talent, driving architectural and roadmap decisions, delivering distributed microservices and full-stack systems, and aligning engineering execution with enterprise goals. The role involves AWS and other cloud technologies, modern programming languages, databases, containers, Agile delivery, AI-enabled development, and regulatory technology solutions.

Build infrastructure for AI-driven software development, including cloud coding environments, autonomous coding agents, SRE integrations, and reusable agent platforms. Own developer environments, agent integrations, security guardrails, observability, evaluation, and feedback loops. The role requires deep infrastructure experience across AWS, containers, infrastructure as code, CI/CD, and TypeScript/Node.js, plus hands-on use and orchestration of AI coding agents.

Designs and delivers enterprise web applications using Angular, Java, Spring Boot, microservices, relational and NoSQL databases. Leads system architecture, security, scalability, testing, CI/CD, and production readiness while leveraging AI coding agents. Owns delivery end to end, integrates agentic workflows, manages multiple workstreams, and coaches engineers in AI-first development. Applies Corporate and Investment Banking knowledge to deliver business-focused technology solutions.

Lead the architecture and modernization of Citi’s cross-asset XVA valuation, risk, and stress-testing platforms. Drive distributed systems, cloud-native migration, Java and Python engineering, AI-enabled development, agentic workflows, MLOps, and legacy modernization. Partner with quants, trading desks, and risk teams to deliver scalable production systems while overseeing regulatory compliance, resiliency, governance, Agile execution, and globally distributed engineering teams.

Leads the design, development, and deployment of scalable full-stack applications for M&A technology using Java, Angular, microservices, and event-driven architectures. Integrates agentic AI, GenAI, and LLM capabilities into regulated enterprise systems. Oversees software lifecycle activities, cloud and DevOps practices, security, testing, operational readiness, and risk. Mentors developers, conducts code reviews, partners with architecture and business stakeholders, and promotes modern engineering standards.

Build, test, deploy, and maintain secure, scalable full-stack enterprise applications and prototypes. Develop front-end experiences, backend services, APIs, integrations, authentication, and data persistence. Use AI coding assistants and integrate generative AI, RAG, agents, and tool calling when appropriate. Operate cloud-native solutions with CI/CD, infrastructure as code, automated testing, observability, and security controls. Collaborate with product managers and architects, troubleshoot production systems, document solutions, and communicate technical risks and tradeoffs.

Build, test, deploy, and operate secure, scalable full-stack enterprise applications. Lead technical delivery for a workstream or small team, mentor engineers, conduct code reviews, and guide architecture and design decisions. Develop cloud-native services with CI/CD, infrastructure as code, observability, and enterprise security controls. Integrate generative AI, RAG, agents, and tool calling, evaluating solution quality, cost, latency, and security while collaborating with product managers, architects, IT, and business stakeholders.

Develop AI agents and secure MCP servers for IAM and enterprise applications. Build Python and Node.js backend services, REST APIs, and modern React or Vue.js interfaces. Integrate LLMs and generative AI into existing workflows while applying prompt engineering, tool integration, security, scalability, and performance best practices. Collaborate with engineering and product teams to deliver AI-powered enterprise solutions.

The Principal Software Development Engineer leads the architecture and delivery of AI-driven healthcare applications, overseeing full stack development and collaborating with stakeholders to align technical solutions with business needs.

Leads development of a next-generation equipment and asset finance platform. Designs, builds, tests, secures, and troubleshoots scalable Java and Spring Boot applications using microservices, REST, Kafka, React, and relational databases. Provides technical direction to a global feature team, mentors engineers, reviews code, drives AI-assisted engineering practices, and contributes to architecture. Improves application stability, observability, code quality, deployment reliability, and operational support across development, staging, and production environments.

Own and evolve the AI Accountant’s full-stack systems, with emphasis on backend architecture, reliable third-party data ingestion, idempotent processing, background jobs, account synchronization, and production operations. Integrate LLMs and ML into classification and reconciliation workflows with strong validation and failure handling. Design PostgreSQL schemas and ensure transactional correctness while shipping frequently and owning systems end to end.

Lead development of AI infrastructure for large-scale GPU training and inference. Design workload scheduling, serving, orchestration, resource governance, failover, and multitenant Kubernetes platforms. Build reliable C# and Go services, optimize GPU fleet performance, and drive observability, diagnostics, and production operations. Provide technical leadership, architectural direction, mentoring, and cross-team collaboration across cloud infrastructure, hardware, networking, and AI deployment teams.

Lead the vision, architecture, and hands-on development of Epiq’s data and AI platforms. Manage a distributed team of 80–100 engineers, establish software engineering standards, and deliver scalable cloud-native services, data pipelines, governance, quality, and AI-ready foundations. Partner with Product, AI/ML, Analytics, and business stakeholders on APIs, event-driven systems, data integration, observability, model operations, GenAI, vector search, and responsible data practices.

Design and implement compiler transformations, distributed runtimes, pipeline parallelism, sharding, and communication-computation overlap for large-scale deep learning training on GPU clusters. Develop JAX and XLA integrations, optimize compiler and runtime performance, support open-source JaxPP, collaborate with framework and hardware teams, and debug large training workloads.

Leads multiple engineering teams building internal platforms, web applications, AI-powered workflows, integrations, data pipelines, and automation. Sets technical direction, oversees architecture and delivery, partners with product and business stakeholders, and develops engineering talent. The role emphasizes front-end development with TypeScript and React, CMS integrations, internationalization and localization, scalable SaaS systems, AI-enabled marketing workflows, and operational productivity improvements.

As a Backend/AI Engineer, you'll integrate LLMs, optimize document processing pipelines, and improve API design for document understanding tasks.

Build and maintain backend services and APIs powering LangSmith’s AI observability, tracing, monitoring, and evaluation workflows. Design scalable architectures, optimize storage and query performance for high-volume data, ensure reliability through testing and monitoring, troubleshoot production issues, and collaborate with cross-functional teams on new features and technical documentation.

Build automation for NVIDIA switches and InfiniBand fabrics, including configuration management, drift reconciliation, NAT gateways, L4 load balancing, and resilient network control loops. Define large-scale network behavior around BGP, convergence, failover, and production failures. Lead technical direction, design standards, and customer deployments while writing production software in Go or Python for AI infrastructure.

Design and optimize high-performance AI compute kernels for GEMM, attention, normalization, convolution, and related primitives. Improve throughput, latency, memory behavior, and precision across heterogeneous hardware. Integrate kernels with Triton and PyTorch, profile workloads using performance tools, evaluate mixed-precision formats, and collaborate with compiler, runtime, and hardware teams on ISA and memory architecture co-design.

Designs and delivers customer-facing API integrations, ETL pipelines, webhook automations, and AI-assisted workflows for nonprofit organizations. Owns discovery, architecture, development, testing, deployment, documentation, monitoring, and iteration. Productizes repeatable solutions into scalable service offerings, collaborates with Sales, Customer Success, and Product, and contributes to scoping, pricing, revenue reporting, and product feedback.