Senior AI Engineer - US
Typeform is hiring a Senior AI Engineer - US for a remote role open to applicants in United States. Level rates it ; you can apply on Typeform.
Level's read on this job
- On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions LangChain, LangGraph and Bedrock among its tools and skills.
- Level classes it as a senior role.
- Typeform has 10 other open roles on Level.
AI in this role
Who we are
Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year—and integrates with essential tools like Slack, Zapier, and Hubspot.
Typeform is fully remote by design. For this role, we can hire candidates based in the ET timezone in the US.
About the team
The AI Engineering team builds the systems and capabilities behind Typeform’s AI products, including Research Flow, our platform for combining quantitative research with deeper qualitative insights.
We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways.
Through Research Flow, this includes helping customers design studies, run AI-moderated conversations with adaptive follow-up questions, and turn responses into useful insights.
The team owns the journey from experimentation through to production. This includes AI application development, evaluation, infrastructure, deployment, observability, reliability, and performance.
You will work closely with Product Managers, Software Engineers, Data Scientists, Data Engineers, and Analytics teams to turn promising AI ideas into secure, scalable, and dependable customer experiences.
About the role
As a Senior AI Engineer at Typeform, you will be instrumental in building and evolving the AI capabilities behind Research Flow, alongside our broader AI products.
Your work will help customers understand the “why” behind responses and move from research questions to informed decisions faster.
Your scope will span generative AI applications, enterprise RAG systems, agentic workflows, model evaluation, machine learning pipelines, and the infrastructure required to run them reliably at scale.
This is a hands-on engineering role with strong ownership. You will turn ideas and prototypes into production systems used by our customers, with direct influence on their quality and performance. You will also help define the technical standards for developing, evaluating, deploying, and monitoring AI across Typeform.
Things you will do
Build and deliver AI products
- Design, build, and deploy generative AI capabilities across Typeform’s products, with a key contribution to Research Flow.
- Develop applications using large language models, RAG, vector search, and agentic systems.
- Build services and APIs that allow product teams to integrate AI capabilities into customer experiences.
- Turn prototypes into reliable production systems with clear measures of performance and quality.
- Explore new ways for customers to collect, understand, and act on information using AI.
Build scalable AI systems
- Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS.
- Build reliable pipelines for batch and real time processing using technologies such as Kafka and Airflow.
- Design solutions using vector databases to support retrieval, recommendations, personalisation, and semantic search.
- Use MLflow to manage experiments, model versions, registries, and deployments.
- Improve the reliability, performance, scalability, and cost efficiency of our AI systems.
Evaluate and improve AI quality
- Build automated evaluation pipelines for generative AI applications, including the conversational and analytical capabilities behind Research Flow.
- Develop benchmarks that measure accuracy, relevance, reliability, fairness, latency, and cost.
- Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking.
- Monitor AI systems in production and identify opportunities to improve their quality and performance.
- Create safeguards that reduce unexpected behaviour and protect customer data.
Shape our AI engineering practice
- Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems.
- Help teams make informed decisions about models, frameworks, infrastructure, performance, and cost.
- Apply strong engineering practices across testing, security, observability, version control, and deployment.
- Share technical knowledge and support the development of other engineers.
- Keep up with relevant AI research, tools, and engineering practices, applying what is useful to Typeform.
Collaborate across Typeform
- Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams to connect AI investments with customer and business needs.
- Work with Data Scientists to turn experiments and models into reliable production services.
- Communicate technical concepts, risks, and tradeoffs clearly to technical and nontechnical partners.
- Contribute to technical planning and help shape the direction of AI across Typeform.
What you bring
- At least four years of experience building and deploying machine learning or AI systems in production.
- Strong Python and software engineering skills.
- Experience building production services using Python frameworks such as FastAPI.
- Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems.
- Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.
- A strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.
- Experience creating automated evaluations for generative AI applications.
- Experience with AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.
- Experience using services such as AWS SageMaker or AWS Bedrock.
- Experience with Kafka, vector databases, or other technologies used for real time and high dimensional data processing.
- Experience managing machine learning workflows using MLflow.
- Experience monitoring production systems with tools such as Datadog or OpenSearch.
- The ability to balance quality, speed, reliability, scalability, and cost when making technical decisions.
- Strong communication skills and experience collaborating with Product, Engineering, and Data teams.
Extra awesome
- Experience working in a B2B SaaS product company.
- Experience with orchestration tools such as Airflow or Argo Workflows.
- Familiarity with SQL, Spark, Snowflake, or other data processing technologies.
- Experience building systems that combine structured data, unstructured data, and generative AI.
- Experience with AI security, privacy, responsible AI, prompt injection protection, or data leakage prevention.
- Experience improving the latency and cost of AI systems operating at scale.
*Typeform drives hundreds of millions of interactions each year, enabling conversational, human-centered experiences across the globe. We move as one team, empowering our collective efforts by valuing each individual’s unique perspective. This fosters strong bonds grounded in respect, transparency, and trust. We champion our diverse customer base by anticipating their needs and addressing their challenges with priority. Committed to excellence, we hold high expectations for ourselves and each other, continuously striving to deliver exceptional results.
We are proud to be an equal-opportunity employer. We celebrate diversity and stand firmly against discrimination and harassment of any kind—whether based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or expression, or veteran status. Everyone is welcome here.
How we rate this
Senior AI Engineer - US at Typeform rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $184k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Evaluation, AI Safety, and AI Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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