Top Remote Software Engineer Jobs in Las Vegas, NV

Designs and implements analytics and query capabilities in Elasticsearch, develops data-intensive features, resolves complex bugs, optimizes data structures and algorithms, and contributes modern Java code. Collaborates autonomously with globally distributed engineering, UI, solutions, and open-source communities. Provides technical expertise, guides projects from design through delivery, and uses AI to accelerate development, debugging, and code optimization.

Leads the technical vision, architecture, development, and delivery of FOS software products. Manages and scales engineering teams, drives modernization from legacy to modern technology stacks, oversees cloud, microservices, APIs, CI/CD, quality, security, and reliability practices, and collaborates with product and business stakeholders. The role also supports talent recruitment and development, compliance with SOC 2 requirements, disaster recovery planning, and continuous engineering improvement.

Lead an engineering team delivering automated month-end close pipelines for client accounting teams. Oversee ERP integrations, SQLMesh and DuckDB transformations, journal-entry outputs, controls, reconciliations, exception handling, and approval workflows. Maintain architectural boundaries across Elixir, Python, and platform components while converting bespoke client solutions into reusable capabilities. Manage technical roadmaps, multiple client engagements, engineering standards, and team development while partnering with accounting, delivery, technology, and product stakeholders.

Develop full-stack mission planning and command-and-control software for space communications programs. Build responsive interfaces with modern JavaScript frameworks, backend services and APIs using Python and SQL, and containerized applications. Own features through testing and deployment, write automated tests, collaborate with QA and cross-functional teams, and improve software usability, security, performance, and reliability in highly secure government environments.

Join a remote engineering team to write, test, and maintain code under senior guidance; participate in code reviews, standups, and sprint planning; debug and resolve application issues; and continuously learn new technologies and best practices.

Develop, test, implement, optimize, and maintain scalable software systems. Collaborate with product managers, designers, and engineers; troubleshoot technical issues; conduct code reviews; contribute to architecture decisions; follow secure coding practices; and participate in Agile ceremonies.

Build full-stack AI-powered video creation and collaboration tools, including rich multimedia interfaces, backend APIs, server-side processes, LLM-powered features, and conversational experiences. Work with generative AI, computer vision, and machine learning models in production. Improve system performance, reliability, and code quality while rapidly prototyping and delivering product features in a collaborative, high-ownership environment.

Lead delivery and technical execution for an AI-driven pipeline integrity platform spanning data architecture, engineering, data science, application engineering, and QA. Remain hands-on through coding, design reviews, prototyping, debugging, and quality oversight. Manage compliance, security, audit readiness, release planning, hiring, team development, and cross-functional collaboration. Ensure platform outputs are traceable, reproducible, secure, and delivered predictably against phased milestones.

Design, implement, and operate features for Temporal’s open source distributed systems server. Solve challenges involving scheduling, task processing, workflow execution, persistence, quotas, visibility, and performance. Improve reliability through testing, observability, dashboards, alerts, runbooks, and documentation. Collaborate across engineering and product teams, participate in design reviews, contribute to developer experience, and mentor junior engineers.

Lead development of high-performance Rust parsers, compilers, automata, indexes, and data structures for structured language-model generation. Optimize decoding-loop performance through profiling and benchmarking, integrate Python bindings and C++/CUDA components into inference engines, collaborate across teams, and maintain production-quality code through testing and CI/CD.