About Understood

Understood is a nonprofit focused on shaping the world for difference. We raise awareness of the challenges and strengths of people who learn and think differently. Our resources help people navigate challenges, gain confidence, and find support and community so they can thrive. 

Having a shared commitment to our values is a key factor in any hire we make. We have five core values: 

1. Continuously learn.
2. Act with intention.
3. Champion difference.
4. Inspire change.
5. Grow together. 

Come be part of an organization with an entrepreneurial spirit that’s helping to shape the world for difference. Together, we can build a world where everyone can reach their full potential. 

To learn more about Understood, please visit: www.understood.org.

Who you are 

To advance Understood’s mission and further our impact, we’re hiring a Senior Full-Stack Engineer, reporting to an Engineering Manager, to work across our frontend, backend, and AI systems. You’ll join a cross-functional team and collaborate closely with product, design, data, and content teams to build and evolve the platforms that power Understood.org and our AI-assisted experiences.

The ideal candidate is comfortable working across the stack—from React and Next.js on the frontend to Python and Django on the backend—and brings demonstrated experience with LLM-powered products. You’ll contribute to a growing portfolio of AI tools, including our conversational assistant and emerging multimodal experiences, while helping millions of families navigate learning and thinking differences.

This is a hybrid role that requires a minimum of three (3) days a week in our NYC office, with a focus on Monday, Tuesday, and Thursday. We are a Mac-based environment, and team members are provided a Mac laptop for their work. 

What you’ll do

• Collaborate with cross-functional teams (product, design, data, content) to design, develop, and maintain features across the full stack
• Build high-quality, accessible frontend experiences in Next.js, React, and TypeScript, including the stateful, streaming chat and multimodal (voice, text-to-speech, speech-to-text) interfaces that power our AI assistants.
• Architect and ship the backend services and APIs (Python, Django, SQL) behind them, including integrations with PostgreSQL, Redis, Pinecone, and Contentful.
• Monitor and improve AI performance KPIs, including system latency and time-to-first-token (TTFT)
• You know how to build accessible and localized products
• Own your work across the entire software development lifecycle, from architecture and planning through development, deployment, and monitoring
• Ship early and often. Break big problems into small, releasable increments and get them in front of users using feature flags, A/B tests, and progressive rollouts rather than big-bang launches.
• Stay close to the people we serve. Dig into user feedback, support tickets, and product analytics to find the real problem, then ship the smallest change that solves it.
• Leverage tools such as DataDog, Sentry, and Langsmith for monitoring, alerting, and analytics to proactively identify and resolve issues; own your services’ health
• Collaborate effectively with both internal teams and external development partners to co-design solutions, troubleshoot integrations, and review code
• Participate in code reviews, mentor junior engineers, and contribute to continuously improving development processes and best practices
• Stay current with emerging technologies and industry trends, advocating for tools and practices that enhance our development process and product offerings

Must-haves 

• 7+ years of professional experience delivering production software, with meaningful depth in both frontend and backend development
• Strong expertise in TypeScript, React, and Next.js, including experience building stateful, streaming interfaces
• Demonstrated  experience with Python and Django (or equivalent backend frameworks)
• Proficiency in designing and building RESTful API’s
• Experience working with relational databases (PostgreSQL, MySQL) and vector databases (Pinecone)
• Comfortable working in the cloud (GCP, AWS, or similar)
• Experience monitoring and instrumenting production services; we use Datadog and expect engineers to own their services’ health
• Demonstrated ability leading projects as a technical lead
• Ability to break complex projects into small, shippable increments and get them in front of real users quickly, using feature flags, staged rollouts, and experimentation platforms (Statsig or similar) to de-risk along the way, rather than sitting on a polished v3.
• Genuine interest in user problems. You read the support inbox, watch session replays, and treat "is this actually working for people?" as part of the definition of done.
• Excellent communication skills, particularly when explaining technical matters to non-technical stakeholders and more junior engineers
• Thrives in a collaborative environment and is motivated to promote a culture of teamwork, knowledge sharing, and continuous improvement
• Familiarity with observability tooling beyond basic monitoring (distributed tracing, log analytics)

Nice-to-haves

AI & Personalization

• Production experience with LLM orchestration and agent design: LangChain / LangGraph / LangSmith or equivalents, multi-agent routing, memory and personalization layers (LangMem or similar), and Model Context Protocol (MCP).
• A practical approach to making LLMs reliable in production: prompt engineering and tuning, systematic evaluation of outputs, guardrails and fallbacks, and designing around hallucinations and other failure modes.
• Experience with retrieval-augmented generation (RAG) and vector databases (Pinecone, Weaviate, pgvector, or similar).
• Experience building real-time, multimodal AI experiences (streaming text, voice, TTS/STT, Web Audio, WebRTC, real-time OpenAI SDKs), including optimizing latency and time-to-first-token (TTFT) in production.

Trust, Safety & Compliance

• Experience building or contributing to trust and safety systems (content moderation, input/output filtering, guardrails for AI-generated content)
• Familiarity with privacy-by-design principles, data classification, and consent management in user-facing products
• Understanding of compliance frameworks relevant to health-adjacent or child-focused digital products (e.g., COPPA, state companion-app laws, SOC 2, ISO 42001)

General

• Experience with Contentful
• Experience with asynchronous programming and task queues
• Experience with Docker and/or Kubernetes
• Proven ability to collaborate with and integrate code from external development agencies or contractors
• Experience with React Native or mobile app development
• A background in the nonprofit sector or a strong passion for using technology for social good

The base salary range for this role is minimum $155,000 - $175,000 maximum, depending on years of experience and qualifications. We offer a comprehensive benefits package that supports wellness for our team members and their families. You can learn more about our benefits and offerings.

Understood.org does not sponsor applicants for work visas or legal permanent residence, including providing assistance with OPT extensions.

Commitment to diversity, equity, and inclusion

Understood encourages individuals of all learning styles and ethnic, racial, and socioeconomic backgrounds, including those whose life experiences may include the challenge of access due to a disability, to apply for this position. We are committed to maximizing the diversity of our organization, as we want to engage all those who can contribute to supporting this work.

Understood is an equal opportunity employer and considers all applications without regard to race, color, religion, creed, sex, national origin, ancestry, age, alienage or citizenship status, marital or familial status, domestic partnership status, caregiver status, sexual orientation, gender, gender identity or expression, change of sex or transgender status, genetic information, medical condition, pregnancy, childbirth or related medical conditions, physical or mental disability (where the applicant or employee is qualified to perform the essential functions of the job with or without reasonable accommodation), any protected military or veteran status, or status as a victim of domestic or dating violence, sexual assault or offense, stalking, or any other characteristics protected by federal, state, or local law or that of persons with whom that individual associates, or any other legally protected characteristics.

For additional information on learning and thinking differences, including ADD/ADHD, dyslexia, dyscalculia, dysgraphia, dyspraxia, executive function challenges, nonverbal learning disabilities, processing issues, and more, please visit www.understood.org.

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About the role

We're building the infrastructure that lets people talk to Claude—real-time, bidirectional voice conversations that feel natural, responsive, and safe. This is foundational work for how millions of people will interact with AI.

The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems—building infrastructure where every millisecond of latency is felt by the user.

We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.

What you'll do

• Design and build the real-time streaming infrastructure that powers voice conversations with Claude—ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency
• Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness
• Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers
• Own the audio transport layer—codecs, jitter buffers, adaptive bitrate, packet loss recovery—so conversations stay smooth across unreliable networks
• Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy
• Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research
• Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience

You may be a good fit if you

• Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale
• Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss
• Are comfortable working across the stack—from transport protocols and serving infrastructure up to the APIs product teams build on
• Are results-oriented, with a bias toward flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly
• Are comfortable with ambiguity—voice is a fast-moving space, and you'll help define the architecture as we learn what works

Strong candidates may also have experience with

• Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale
• Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP
• Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure
• Telephony, live streaming, video conferencing, or voice assistant platforms
• Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)
• Working alongside ML researchers to productionize models—speech experience is a plus but not required

Representative projects

• Driving time-to-first-audio below human perceptual thresholds by co-designing the serving pipeline with the Audio research team
• Building a streaming inference orchestrator that interleaves speech recognition, LLM reasoning, and speech synthesis with overlapping execution
• Designing the voice mode API surface for the Anthropic API so developers can build their own voice agents on Claude
• Implementing graceful barge-in and interruption handling so users can cut Claude off mid-sentence naturally
• Instrumenting end-to-end audio quality metrics and building dashboards that catch regressions before users do

Deadline to apply: None. Applications will be reviewed on a rolling basis.