Note: The job is a remote job and is open to candidates in USA. AssemblyAI is a leading company in Voice AI technology, seeking an Applied AI Engineer to bridge AI research and customer applications. The role involves building demos, troubleshooting issues, and collaborating with various teams to enhance customer success with Speech AI models.
Responsibilities
- Guide customers through their entire product journey—from initial implementation and technical onboarding, through development and testing, all the way to production deployment. Continue to provide support post-launch to ensure their implementation is performing optimally and meeting their business objectives
- Build custom demos and prototypes that showcase how AssemblyAI's models can solve specific customer use cases
- Lead technical discovery sessions with prospects and customers to understand their requirements and design optimal implementations
- Assist with competitive evaluations by providing benchmarks, designing fair comparison tests, and helping customers evaluate our models against alternatives. Work closely with customers to ensure they have the data and support needed to make informed decisions
- Troubleshoot production issues for customers using our streaming and async APIs, sometimes requiring you to debug code in languages you may not use daily (Java, Go, Ruby, etc.)
- Provide technical guidance on architecture, scaling, data privacy, and best practices for integrating our APIs
- Create proofs-of-concept that demonstrate the "art of the possible" with Speech AI
- Travel to customer sites for technical workshops, implementation support, and relationship building with key accounts
- Serve as the voice of the customer to our Product and Research teams—test and dogfood new products and features before they reach customers, providing feedback from a practitioner's perspective. Advocate for improvements and new capabilities based on real-world use cases you encounter, ensuring our roadmap aligns with customer needs
- Contribute to documentation, guides, and example code that help developers integrate our APIs more effectively
- Identify patterns in customer issues and work with Engineering to address root causes (SDK improvements, better error messages, new features)
- Collaborate with Sales and Success teams to ensure smooth handoffs and consistent customer experience
- Participate in team off-sites to align on strategy, share learnings, and build team cohesion
- Stay current on AI/ML developments, particularly in speech recognition, NLP, and audio processing
- Experiment with new use cases and applications of our models
- Build and maintain an open-source repository of demos, integrations, and reference implementations
- Represent AssemblyAI at conferences and industry events, delivering talks or running workshops when appropriate
Skills
- Located in or willing to relocate to New York City or San Francisco
- 4+ years of customer-facing experience in highly technical environments, requiring strong software engineering skills, including roles such as Solutions Architect, Developer Advocate, Technical Solutions Engineer, or equivalent
- Strong programming skills in Python and/or TypeScript/JavaScript, with the ability to read and debug code in other languages
- Excellent written and verbal communication skills—you're writing customer emails, internal documentation, and technical guides regularly
- Experience with web APIs, WebSockets, and real-time data streaming
- Understanding of audio fundamentals (sample rates, encoding formats, codecs) or willingness to learn quickly
- Ability to leverage AI tools creatively to move quickly—proficiency with tools like Claude, Cursor, Windsurf, or similar AI-assisted development tools to accelerate prototyping, debugging, and problem-solving
- Problem-solving mindset—you can debug unfamiliar codebases, identify root causes, and propose creative solutions
- Comfort with ambiguity and fast-paced work—you'll often be the first line of defense on novel problems
- Ability and willingness to travel domestically and internationally as needed (approximately 10-25% of the time)
- Experience in a startup or high-growth environment
- Understanding of cloud infrastructure (AWS, GCP, Azure) and deployment patterns
- Experience building prototypes or MVPs quickly
- Public speaking or conference presentation experience
Company Overview
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