Senior Software Engineer, Go - LLM Team

About AssemblyAI AssemblyAI builds the best-in-class Speech AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences—from voice agents and meeting assistants to contact centers and medical scribes. Companies like Zoom, Granola, Fireflies, Cluely, and Calabrio rely on AssemblyAI to ship production-ready voice AI. We're at an inflection point in Speech AI. We released Universal-Streaming in mid-2025, and it has quickly earned its place as the model offering the best accuracy-latency-cost tradeoff on the market. Our research team drives these advances and ships with relentless velocity. Since releasing Universal-Streaming, we've already launched keyterms prompting feature and multilingual support—with more significant improvements on the roadmap. We've raised $115M+ from Accel, Insight Partners, Y Combinator's AI Fund, Patrick and John Collison, Nat Friedman, and Daniel Gross. We're a remote team building one of the next great AI companies—and we're looking for researchers who will shape its future. About the Role We're seeking an exceptional Senior Software Engineer to join our LLM team. This role is focused on building and maintaining our LLM gateway service—a unified API platform that connects customers to multiple LLM providers. You'll work on high-impact projects that directly solve customer problems, improve their AI and agentic workflows, and ensure reliable access to the best models for their use cases. This is a deeply customer-focused role. You'll work closely with our customer success team to understand customer challenges, help optimize their prompt strategies, build features that address their pain points, and ensure our service reliably delivers value. We're looking for someone who combines software engineering excellence with genuine curiosity about how customers use AI and a drive to make their lives better. As a Senior Engineer, you'll drive technical execution within the team, taking ownership of significant features and integrations while mentoring more junior engineers. You should be passionate about writing clean, maintainable code, implementing comprehensive testing strategies, and building highly reliable systems in service of solving real customer problems. This role requires close collaboration with customer success, product managers, external API providers, and other engineering stakeholders. You'll need to balance technical excellence with pragmatic delivery in a fast-paced startup environment where uptime, reliability, and customer success are critical. What You'll Do Solve Customer Problems Partner closely with the customer success team to understand customer use cases, challenges, and integration needs Translate customer pain points surfaced by the CS team into technical solutions and product improvements Build features and tooling that directly address customer needs and improve their workflows Provide technical guidance and expertise to the customer success team to help them support customers effectively Drive Technical Execution Own and deliver complete features and integrations within our LLM gateway service Build and maintain integrations with multiple LLM providers and AI services (OpenAI, Anthropic, Google Vertex, AWS Bedrock etc.) Write clean, maintainable, well-tested code following best practices Design and implement scalable, fault-tolerant solutions with appropriate abstractions Proactively identify and address technical debt, reliability issues, and code quality concerns Participate in on-call rotation to ensure service reliability and rapid incident response Elevate Engineering Standards Conduct thorough code reviews focused on maintainability, testing, reliability, and architectural concerns Ensure proper test coverage across unit, integration, and end-to-end testing levels Improve code maintainability and extensibility through targeted refactoring Contribute to runbooks, incident postmortems, customer-facing documentation, and knowledge sharing Identify bottlenecks and propose solutions to improve team velocity and system reliability Build and Collaborate Work closely with product, customer success, and engineering teams to deliver solutions Collaborate with external API providers to troubleshoot integration issues and improve reliability Translate ambiguous customer requirements into well-scoped technical work Proactively communicate status, risks, and blockers Mentor junior engineers on coding standards, reliability practices, and customer-centric thinking Participate in architectural discussions and contribute to technical decisions What You'll Need Core Requirements 5+ years of professional software engineering experience Strong proficiency in Go with demonstrated ability to write production-quality code Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and understanding of prompt engineering concepts Experience building or working with API gateways, proxies, and rate limiting systems Deep experience with prompt engineering, chain-of-thought, few-shot learning, and other LLM optimization techniques Experience building applications with llms or ai agents with cascading architectures Solid understanding of software engineering fundamentals: Data structures and algorithms System design and architectural patterns Testing strategies (unit, integration, end-to-end) Code review practices and technical collaboration Experience with: RESTful APIs and distributed systems concepts Building or integrating with third-party APIs SQL and database design Version control (Git) and CI/CD pipelines Containerization (Docker) and cloud infrastructure Strong communication skills and ability to collaborate effectively with cross-functional teams Track record of delivering high-quality, reliable software in a fast-paced, team environment Ability to thrive in a startup environment with changing priorities and rapid iteration Nice to Haves Experience with AWS services (ECS, Lambda, ElastiCache/Redis, RDS, S3, CloudWatch, API Gateway) Experience with monitoring and observability tools (Datadog, CloudWatch) Experience with request routing, load balancing, and traffic management Experience with circuit breakers, retry logic, fallback strategies, and fault tolerance patterns Understanding of API design, versioning, and backward compatibility Experience working closely with customer success or support teams What We're Looking For This role requires someone who is: Customer-obsessed - You genuinely care about solving customer problems and making their lives easier, working through the customer success team to understand and address their needs Excellent at software fundamentals - You write code that others want to emulate Quality-focused - You care deeply about testing, documentation, and maintainability Reliability-obsessed - You understand that uptime and performance directly impact customer trust LLM-savvy - You understand prompt engineering, model capabilities, and how to help customers get the best results Integration-savvy - You've wrestled with third-party APIs and know how to build resilient integrations Collaborative - You work well with diverse stakeholders and partner effectively with customer success teams Communicative - You can explain complex technical concepts clearly to teammates and cross-functional partners Growth-minded - You're curious, eager to learn, and want to expand into platform and infrastructure engineering Pragmatic - You balance perfection with delivery and understand trade-offs Team-oriented - You improve not just the code, but the team's overall effectiveness Proactive - You anticipate problems before they become incidents and build systems defensively Empathetic - You put yourself in the customer's shoes and design solutions accordingly We're looking for the best person for this role - someone who can hit the ground running while growing with the team. The ideal candidate brings strong software engineering discipline, a passion for AI/LLMs, and genuine excitement about solving customer problems through reliable, thoughtfully designed infrastructure. Pay Transparency: AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity across our team. Our salary ranges are set to be competitive for our size, stage, and industry, and reflect just one component of the full compensation, benefits, and rewards we offer. Salary determinations consider a variety of factors, including relevant experience, technical depth, skills demonstrated during the interview process, and maintaining internal equity with peers on the team. The range shared below represents a general expectation for the posted position. However, we are open to considering candidates who may fall above or below the outlined experience level—in those cases, we will communicate any adjustments to the expected salary range. The range provided applies to candidates located in the United States. For candidates outside of the U.S., compensation ranges may differ; any adjustments will be communicated throughout the interview process. Salary range: $180,000 - $240,000 The expected base compensation for this role is listed above. Our total compensation package includes competitive equity grants, 100% employer-paid benefits, and the flexibility of being fully remote. 401k match up to 4% for US-based full time team members. Working at AssemblyAI We are a small but mighty group of startup veterans and experienced AI researchers with over 20 years of expertise in Machine Learning, Speech Recognition, and NLP. As a fully remote team, we’re looking for people to join our team who are ambitious, curious, and lead with integrity. We’re still in the early days of AI and of AssemblyAI’s journey, and are looking for teammates who won’t just fit in, but will help us define and build our company culture. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply! Using AI to Interview: If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process. GDPR privacy notice: Candidates from the EU should review this job applicant privacy notice before applying. Keep Exploring AssemblyAI: Keep Exploring AssemblyAI: Check us out on YouTube! Learn more about AI models for speech recognition Speech-to-Text | Speech Understanding | LLM Gateway | Try the Playground Our $50M Series C fundraise