Apply on company website San Francisco; Bellevue; New York On-site Full-time USD 175,000 – 280,000 / year

Sesame is hiring a Software Engineer - Backend

About Sesame Sesame believes in a future where computers are lifelike - with the ability to see, hear, and collaborate with us in ways that feel natural and human. With this vision, we're designing a new kind of computer, focused on making voice agents part of our daily lives. Our team brings together founders from Oculus and Ubiquity6, alongside proven leaders from Meta, Google, and Apple, with deep expertise spanning hardware and software. Join us in shaping a future where computers truly come alive. About the Role Backend engineering at Sesame is a domain rich with challenging technical problems: real-time streaming audio pipelines, resilient and low-latency networking, complex machine learning inference, scalable agentic workflows, and more. Our work ranges from systems programming to thorny distributed systems design to cutting-edge applied AI. At the centre of all of this: how should we think about quality, craft, security, and reliability engineering when the system under test is a human-like personality? On the backend engineering team, your job is to tackle challenges like these directly, all while providing a reliable, secure, high quality consumer experience for a growing base of users. Responsibilities Design and build the backend systems and services that power Sesame's product. You own the data models, the APIs, and the distributed systems that everything else depends on Write software that's built to last. You're not prototyping; you're solving hard problems that require careful thinking about scalability, reliability, and correctness Build and evolve the frameworks and libraries that other engineers build on. You care about good software design and it shows in the interfaces you create Own the full lifecycle of your services: schema design, implementation, deployment, performance tuning, and on-call Work across the data layer, choosing and operating the right stores for the job: relational databases, NoSQL, queues, caches, search indexes Identify performance bottlenecks and fix them. Think about cost, throughput, and latency as first-class concerns Own the architecture of systems where ML models are a critical component but not the whole story. Real-time audio pipelines, agentic orchestration, stateful conversation systems — these are complex, ML-driven machines that require careful architecture Spot opportunities to improve developer efficiency within your area. You might prototype a tool or workflow improvement, then hand it off to the infra team to productionize Required Qualifications You're a strong programmer first. You're expert-level in at least one language and you write clean, well-designed code that other engineers can build on Solid distributed systems fundamentals. You can think through system models, failure modes, consistency tradeoffs, and scaling strategies independently You've designed and built systems that handle real scale. Caching layers, sharded data stores, async processing pipelines, shared-nothing service architectures — you've worked with these patterns in production environments, not just theoretically Strong database engineering skills. You've built complex schemas, tuned queries, and made hard choices about data modeling across relational and non-relational stores Comfortable with protocols and networking at the application level: REST, WebSockets, gRPC, HTTP semantics. You understand how services talk to each other and you make good choices about it You deploy and run services on Kubernetes. You're self-sufficient here, but you're not the person setting up the cluster Proven reliability engineering instincts. You've been on challenging on-call rotations and you came out of them with ideas for how to make things better You have a genuine deep interest in some area of software. Maybe it's software design, CRDTs, real-time systems, database internals, or something else entirely. You go deeper than the job requires because you want to Preferred Qualifications We'd love to hear about experience in any of these areas — but we don't expect any one person to have all of them: Hands-on experience in one or more of these domains: Payments — billing systems, transaction processing, ledgers, financial data integrity Search and relevance — building and tuning search infrastructure, ranking, indexing pipelines Real-time media — streaming, low-latency audio/video, real-time communication systems Deep Python expertise. You know how to write Python that's maintainable, performant, and scalable Experience building on GCP Sesame is committed to a workplace where everyone feels valued, respected, and empowered. We welcome all qualified applicants, embracing diversity in race, gender, identity, orientation, ability, and more. We provide reasonable accommodations for applicants with disabilities. Contact careers@sesame.com for assistance. Full-time Employee Benefits: 401 (k) max employer match: 3.5% of compensation 100% employer-paid health, vision, and dental benefits for you and your dependents Unlimited PTO and sick time Flexible spending account with employer matching up to $1,650/year (medical FSA) Guardian Employee Assistance Program (EAP) Opportunity to share in the company's success with competitive stock options Benefits do not apply to contingent/contract workers.
Job Details
Location San Francisco; Bellevue; New York
Work mode On-site
Employment Full-time
Salary USD 175,000 – 280,000 / year
Department Software
Category other
Posted 4 months ago
Application On company website
About company
Sesame logo

Personal intelligence with a point of view. Made to help you do more of what you love.

Sesame is an interdisciplinary team of artists, makers, and engineers focused on bringing ambient intelligence to daily life. We are building personal agents capable of holding natural conversations and devices that make them more effective.

Voice as an interface is nuanced and intimate, which makes it a difficult medium to get right. We believe that a great voice product calls for an interdisciplinary approach that tightly integrates hardware, software, and machine learning.

Deep and innovative machine learning research is essential to our goals. Our research team is actively pushing forward on multiple fronts, including speech generation, personality modeling, and multimodality.

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