Senior Software Engineer – Applied AI Systems

Senior Applied AI EngineerLocation: San Francisco, CAEmployment Type: Full-Time, Direct HireCompensation: $210,000–$260,000 base salary, plus equity and benefitsWorkplace: Onsite five days per weekNote: No C2C arrangements will be considered.Any attempt to use personal or household contact information for solicitation, candidate submission, or vendor outreach is strictly prohibited and will be reported to LinkedIn.About the CompanyOur client is a well-funded applied science company building high-performance distributed data systems for large enterprise customers. Its platform combines advanced neural, graph-based, and causal-computation methods with specialized compute infrastructure to deliver real-time analytical capabilities at significant scale.The company has a small, highly technical engineering organization where individual contributors work closely with applied scientists, product teams, and senior leadership. Engineers have substantial ownership and a short path from identifying a customer need to deploying a production solution.About the RoleWe are seeking a Senior Applied AI Engineer to build and extend the backend systems powering an advanced applied science platform.This is a hands-on software engineering role centered on Python backend services, distributed data systems, and the infrastructure connecting customer-facing products with high-performance compute environments.In this position, Applied AI does not refer to generative AI, prompt engineering, or LLM fine-tuning. The underlying platform uses causal, graph-based, and neural systems developed by an applied science team. Your responsibility will be to make those systems fast, reliable, scalable, and usable in production.This is not a spec-in, spec-out environment. You will work through ambiguity, make practical technical tradeoffs, and partner directly with senior engineers, applied scientists, product teams, and company leadership to determine what should be built and how.What You’ll DoBuild and operate production backend services in Python, including APIs, data services, and integration layers.Connect advanced computation and applied science systems with the products and workflows customers use.Work across backend services, data pipelines, storage, infrastructure, and integration layers as problems require.Translate customer and product requirements into reliable production systems.Partner closely with applied science, data products, infrastructure, and customer-facing teams.Ship iteratively and improve systems based on customer needs and production behavior.Own the reliability, performance, maintainability, and continued evolution of the services you build.Diagnose production issues involving application services, data flows, infrastructure, and system performance.Contribute to technical direction, architectural decisions, code quality, and engineering standards.Mentor earlier-career engineers and help strengthen the team’s development practices.Must-Have QualificationsAt least five years of backend software engineering experience in production environments.Strong Python fundamentals and substantial experience building and operating Python backend services.Experience designing, implementing, and maintaining production APIs and service-oriented systems.Demonstrated ability to work across adjacent areas such as data systems, infrastructure, storage, and integrations.Experience taking ownership of systems from design and implementation through deployment and production support.A track record of shipping effectively in fast-moving environments with incomplete or evolving requirements.Strong troubleshooting, debugging, and systems-thinking skills.Clear written and verbal communication, including the ability to explain technical decisions and tradeoffs.Willingness to work outside a narrow specialty when the problem requires it.Ability to work onsite in San Francisco five days per week.Strongly PreferredExperience designing and operating distributed systems.Experience with performance-sensitive systems where latency, throughput, memory utilization, or resource efficiency matter.Exposure to data-intensive applications, including pipelines, storage systems, analytical workloads, or large-scale data processing.Experience improving the reliability and performance of production backend services.Familiarity with cloud infrastructure, containers, deployment systems, observability, and incident response.Experience collaborating directly with product, infrastructure, customer-facing, or scientific teams.These Skills Are a PlusExperience programming with CUDA or working with CUDA-enabled systems.GPU- or accelerator-adjacent software engineering experience.Experience integrating application services with GPU-based or other specialized compute infrastructure.Background in high-scale, high-performance, parallel, or scientific-computing environments.Experience profiling and optimizing CPU- or GPU-intensive workloads.Familiarity with concurrency, parallelism, memory management, or systems-level performance optimization.Experience partnering closely with applied science or research teams.Familiarity with causal inference, graph-based systems, graph computation, or neural architectures.Experience with high-throughput data platforms or real-time analytical systems.What Success Looks LikeYou will succeed in this role if you can:Take an ambiguous technical or customer problem and turn it into a dependable production service.Move comfortably among Python application code, data systems, infrastructure, and integration layers.Make sound engineering tradeoffs without waiting for a fully defined specification.Build systems that remain understandable and maintainable as the platform evolves.Investigate and resolve production behavior that differs from expectations.Collaborate effectively with scientists, engineers, product partners, and customer-facing teams.Balance speed of delivery with reliability, performance, and long-term system health.Take responsibility for the systems you build rather than handing them off after deployment.Why This OpportunityWork on novel systems connecting advanced applied science with specialized production infrastructure.Build services supporting real-time, performance-sensitive computation at substantial scale.Join a small team where individual engineers have meaningful technical influence.Work directly with senior technical leaders and applied scientists.See a short path from idea or customer requirement to production deployment.Solve difficult backend, distributed-systems, data, and performance problems.Build systems used by major enterprise customers for important business decisions.Receive competitive compensation, equity, and benefits.Work Authorization: Candidates must be currently authorized to work in the United States. This position is not eligible for new or future employer-sponsored work authorization.