Full-Time

Frontend Engineer

Boson Ai

Boson Ai

11-50 employees

Develops scalable AI tools for enterprises

No salary listed

Santa Clara, CA, USA

In Person

On-site at Santa Clara HQ; no remote option.

Bachelor's, Master's

Category
Software Engineering (1)
Required Skills
Agile
JavaScript
UI/UX Design
React.js
NoSQL
Git
RDBMS
TypeScript
Next.js
Firebase
HTML/CSS

Get referred to Boson Ai

See people who can refer or advise you

Requirements
  • Bachelor’s degree in Computer Science or a related field. A Master’s degree is highly desirable.
  • Strong contribution record on GitHub. Please include your GitHub link in your application.
  • 3+ years of substantial experience in full-stack web development, with a proven track record on both client-side and server-side components.
  • Proficient understanding of HTML5 and modern JavaScript/TypeScript.
  • Proficiency in Next.js and React.js for front-end development, with a solid track record of building complex, interactive web applications.
  • Familiar with data visualization frameworks such as D3.js,Chart.js, ECharts, etc.
  • Demonstrated experience in UI/UX design, capable of creating functional, aesthetically appealing, and intuitive user interfaces without external design support.
  • Practical experience with Tailwind CSS, with a strong focus on responsive and adaptive design principles for optimal user experience across devices.
  • Skilled in using real-time state management tools like Convex, Supabase, or Firebase.
  • Familiarity with agile development methodologies and a strong understanding of CI/CD processes.
  • Exceptional problem-solving skills, capable of both independent troubleshooting and collaborative innovation in a dynamic environment.
  • Excellent communication skills, able to effectively convey complex technical details and project progress to team members and non-technical stakeholders.
  • Strong organizational skills with the ability to manage multiple priorities and drive projects forward in a fast-paced startup environment.
Responsibilities
  • Lead the full lifecycle development of our LLM-powered enterprise platforms, focusing on front-end implementations.
  • Design and craft user interfaces and user experiences that are both intuitive and highly engaging, meticulously aligning with project requirements and user feedback.
  • Develop intuitive data visualizations to monitor AI agent behavior, understand model performance, and gain insights from processed data. Utilize visual toolkits to track key metrics, identify patterns, and ensure the reliability and effectiveness of AI agents in enterprise applications.
  • Optimize applications for maximum speed and scalability, ensuring all aspects of the platform are responsive and adapt flawlessly across various devices.
  • Build real-time interactive features on the platform by leveraging both relational (RDBMS) and non-relational (NoSQL) database systems.
  • Implement robust third-party authentication and comprehensive security features to protect user data and ensure platform integrity.
  • Write clean, efficient, and well-documented code, adhering to best practices, coding standards, and project specifications.
Desired Qualifications
  • Public Portfolio of work showcasing interactive web applications or creative projects is highly desirable.
  • Experience integrating directly with machine learning APIs or services, especially those involving large language or multimodal models.
  • Familiarity with MLOps practices or data pipelines.
  • Experience with real-time communication protocols beyond basic API calls (e.g., WebSockets, WebRTC for advanced interactivity).

Boson AI develops large language model tools to power AI-driven experiences in virtual worlds. Its products understand and generate human-like text and are designed for wide use, from individuals to large enterprises. The tools work by combining advanced deep learning with system engineering to create customizable LLM-based applications that can be embedded into various software to personalize storytelling, learning, content creation, and data insights. Boson AI differentiates itself by focusing on tailored experiences in virtual environments across multiple industries, offering scalable solutions through product sales, subscriptions, and licensing. The company’s goal is to provide practical, personalized AI tools that enhance user interactions, storytelling, education, and business intelligence in virtual settings, becoming a leading provider in the AI market.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

Santa Clara, California

Founded

2023

Get referred to Boson Ai

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Boson raised $70 million across two seed rounds, funding aggressive model development.
  • Higgs Audio 3.0 launched March 18, 2026, showing active product cadence.
  • Hackathons in Mountain View and Toronto signal developer traction and hiring pipeline.

What critics are saying

  • OpenAI, ElevenLabs, and Google dominate speech models, compressing Boson AI's pricing power.
  • Boson still lacks visible enterprise customer logos, signaling weak moat and fragile demand.
  • A product miss in 2026 would starve a seed-funded company before series A.

What makes Boson Ai unique

  • Alex Smola and Mu Li anchor Boson AI with deep-dive deep-learning credibility.
  • Higgs STT 3 supports 94 languages and outperforms Whisper v3 large on key languages.
  • Boson distributes through Eigen AI, ByteCompute, and ScitiX, broadening enterprise access.

Help us improve and share your feedback! Did you find this helpful?

Benefits

Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

5%

1 year growth

2%

2 year growth

18%
ScitiX
Jul 9th, 2026
Voice, built in: Boson AI's TTS and ASR models are now live on ScitiX Model Inference.

Voice, built in: Boson AI's TTS and ASR models are now live on ScitiX Model Inference. Venus Yang Speech is the most natural interface there is - and it's quickly becoming the default way people interact with AI. Today ScitiX is excited to announce that two of Boson AI's flagship speech models are available on the ScitiX Model Inference platform: bosonai/tts for text-to-speech, and bosonai/asr for speech recognition. Together they give you both halves of a voice experience - listening and speaking - behind a single API, on infrastructure that's built to be simple, fast, and secure. Meet the Boson AI models. Boson TTS is built for voice chat. It doesn't just read text aloud - it speaks, producing expressive, conversational speech that sounds like a person rather than a narrator. * Expressive & conversational - natural emotion, style, and prosody, with inline control * 100+ languages out of the box * Zero-shot voice cloning - capture a voice from a short sample, no fine-tuning required * $0.05 / minute If you're building voice assistants, agents, audiobooks, or any product where tone matters, bosonai/tts is designed to make the output feel alive. Boson ASR is a state-of-the-art speech recognition model that turns spoken audio into accurate text - reliably, across languages, and even when conditions aren't ideal. * State-of-the-art accuracy on real-world audio * 90+ languages supported * Robust in noisy environments - call centers, mobile, the real world * Streaming support for low-latency, real-time transcription * $0.006 / minute Pair the two and you have a full speech loop: bosonai/asr to understand what users say, bosonai/tts to respond in a natural voice. A platform designed to get you live in seconds. Great models are only useful if you can actually ship them. That's the whole point of ScitiX Model Inference - and it shows up in three places. Simple - discover, view, integrate. Every model on the platform lives in the Model Plaza, a searchable marketplace you can filter by provider, type, context window, and price. The flow is the same for every model: * Find the model - e.g. the bosonai/tts card in the Plaza. * View Details - read the spec, capabilities, pricing, and a ready-to-run code example. * Copy the endpoint and key into your config, set the model name, and you're done. js// config.js - model integration export default {baseURL: 'https://api.scitix.ai/model-api', apiKey: 'sk-scitix- - - - - - - - - - - - - ', model: 'bosonai/tts', // swap to 'bosonai/asr' for speech recognition} The API is OpenAI-compatible, so it slots into the tools and SDKs you already use. Fast - production-ready in seconds, not weeks. There's no provisioning, no model download, no infrastructure to stand up. From browsing the catalog to your first API call is a matter of seconds - any model in the Plaza is production-ready the moment you copy its endpoint and key. Behind the scenes, ScitiX handles the GPU capacity and scaling so your latency stays low as your traffic grows. And switching between models is trivial: the endpoint and authentication never change - the only thing that varies between bosonai/tts and bosonai/asr is the model name in your request. In its internal benchmarks, Boson TTS stays responsive across hardware tiers - first audio comes back in tens of milliseconds, with steady streaming throughput: Note: these figures are from internal test runs (Boson TTS streaming, single concurrent request, 100-sample suite) and are provided for reference only. They are test data, not a performance commitment or SLA, and may vary by workload, configuration, and region. Secure - your keys, your control. Authentication is a single Authorization: Bearer header carrying your API key. On the platform side, keys are always masked, can be rotated or revoked at any time, and account access can be protected with an extra layer of two-factor security plus security notifications. Your credentials stay yours. On the infrastructure side, your workloads run on ScitiX's own footprint: ScitiX operates Tier III+ (T3+) data centers in North America, and expects to complete its SOC 2 Type II certification by the end of 2026 - so the security story extends from your API key all the way down to the facilities your models run in. The takeaway. Boson AI's TTS and ASR give you a complete voice loop - expressive, natural speech and accurate, multilingual transcription - behind one OpenAI-compatible API. ScitiX Model Inference makes that loop simple to adopt, fast to scale, and secure by default, from your API key all the way down to the data center. Whether you're giving a product a natural-sounding voice or transcribing speech across 90+ languages, both models are live on ScitiX today - ready the moment you are.