Wordware
️
Please read first
This is a
full-time, in-person role
based in
San Francisco (Presidio)
- we work from the office
5 days a week .
You must be
based in the Bay Area
or willing to
relocate before starting .
We require
US work authorisation , but are open to
O-1 visa sponsorship
for truly exceptional candidates.
About Wordware
Wordware
is an IDE for building AI agents using natural language. It looks and feels like Notion, but lets you design, test, and deploy AI systems in real time - without writing code. Our mission is to bring structure and joy to human–AI collaboration. We’re building a generational company that empowers the next billion knowledge workers to create with AI - not by writing code, but by expressing intent. We’re backed by Spark Capital, Felicis, and Y Combinator ($30M seed round - the largest in YC history). We work hard, move fast, and don’t take ourselves too seriously. It’s intense, but it’s also fun - at Wordware,
you’ll do the best work of your life alongside people you genuinely like.
What You’ll Do
As an
Applied AI Engineer , you’ll be responsible for building, refining, and scaling the agent systems inside Wordware — from architecture to evals to deployment. This isn’t a research role. We care about what works in production: fast response times, predictable behavior, traceability, and uptime. You’ll work across the stack — with infra, frontend, and product — to make sure the agents users build inside Wordware are robust, useful, and usable. A few examples of what you might work on:
Implement
multi-step, tool-using agents
that hit real APIs and handle retries, auth, timeouts, and edge cases.
Build
RAG pipelines
that support grounded answers from structured and unstructured sources.
Design
agent memory systems
that persist relevant state across runs — e.g. scratchpads, summary buffers, embedding stores.
Add
determinism + replay
to agents so users can trace and debug behaviors step by step.
Own and evolve our
eval framework
— both automated checks and human-in-the-loop scoring.
${your ideas}.
Who You Are
Minimum
3+ years of engineering experience , including time shipping production software.
You've
built and deployed agent-like systems
— multi-step LLM pipelines, tool-using bots, scripted assistants, or similar.
Hands-on experience with: RAG pipelines
(e.g. embeddings, vector DBs, chunking strategies)
Agent memory systems
(e.g. scratchpads, history compression, summarization)
Tool use
and orchestration (e.g. calling real APIs, using plugins, auth flows)
Evaluation
— success metrics, regression testing, and improving agent behavior over time
You write production-grade code and can work across systems without needing a spec.
You thrive in fast-paced, product-first environments where the goal is shipping.
Bonus (not required)
Experience with frameworks like
LangChain ,
CrewAI , or
DSPy
— or strong opinions about why you don’t use them.
Shipped agents that are
live in the wild
— used by customers, not just internal demos.
Familiarity with
LLM ops , tracing, observability, and failure handling.
You’ve been a
founder or early engineer
and care deeply about product quality.
The Process
We keep our process simple. Exceptional candidates go from first touch to offer within 2 weeks . Application Submit your resume and answer a few quick questions. If it looks like a fit, we’ll ask for a
1-minute Loom video : tell us who you are and why you’re excited about Wordware.
15-min intro call Quick check to align on location, motivation, and logistics. If it’s a go, we move fast from here.
45-minute technical interview You’ll build a small full-stack app. We’re looking for fluency, speed, and product sense.
System design interview A deep dive into how you think and architect systems. We’ll walk through a real Wordware problem together.
Final conversation Quick vibe check, answer your questions, and scope out the work trial.
Work trial Paid, in-person, and real — typically 3 days to 2 weeks. You’ll work on something meaningful with us.
#J-18808-Ljbffr
Please read first
This is a
full-time, in-person role
based in
San Francisco (Presidio)
- we work from the office
5 days a week .
You must be
based in the Bay Area
or willing to
relocate before starting .
We require
US work authorisation , but are open to
O-1 visa sponsorship
for truly exceptional candidates.
About Wordware
Wordware
is an IDE for building AI agents using natural language. It looks and feels like Notion, but lets you design, test, and deploy AI systems in real time - without writing code. Our mission is to bring structure and joy to human–AI collaboration. We’re building a generational company that empowers the next billion knowledge workers to create with AI - not by writing code, but by expressing intent. We’re backed by Spark Capital, Felicis, and Y Combinator ($30M seed round - the largest in YC history). We work hard, move fast, and don’t take ourselves too seriously. It’s intense, but it’s also fun - at Wordware,
you’ll do the best work of your life alongside people you genuinely like.
What You’ll Do
As an
Applied AI Engineer , you’ll be responsible for building, refining, and scaling the agent systems inside Wordware — from architecture to evals to deployment. This isn’t a research role. We care about what works in production: fast response times, predictable behavior, traceability, and uptime. You’ll work across the stack — with infra, frontend, and product — to make sure the agents users build inside Wordware are robust, useful, and usable. A few examples of what you might work on:
Implement
multi-step, tool-using agents
that hit real APIs and handle retries, auth, timeouts, and edge cases.
Build
RAG pipelines
that support grounded answers from structured and unstructured sources.
Design
agent memory systems
that persist relevant state across runs — e.g. scratchpads, summary buffers, embedding stores.
Add
determinism + replay
to agents so users can trace and debug behaviors step by step.
Own and evolve our
eval framework
— both automated checks and human-in-the-loop scoring.
${your ideas}.
Who You Are
Minimum
3+ years of engineering experience , including time shipping production software.
You've
built and deployed agent-like systems
— multi-step LLM pipelines, tool-using bots, scripted assistants, or similar.
Hands-on experience with: RAG pipelines
(e.g. embeddings, vector DBs, chunking strategies)
Agent memory systems
(e.g. scratchpads, history compression, summarization)
Tool use
and orchestration (e.g. calling real APIs, using plugins, auth flows)
Evaluation
— success metrics, regression testing, and improving agent behavior over time
You write production-grade code and can work across systems without needing a spec.
You thrive in fast-paced, product-first environments where the goal is shipping.
Bonus (not required)
Experience with frameworks like
LangChain ,
CrewAI , or
DSPy
— or strong opinions about why you don’t use them.
Shipped agents that are
live in the wild
— used by customers, not just internal demos.
Familiarity with
LLM ops , tracing, observability, and failure handling.
You’ve been a
founder or early engineer
and care deeply about product quality.
The Process
We keep our process simple. Exceptional candidates go from first touch to offer within 2 weeks . Application Submit your resume and answer a few quick questions. If it looks like a fit, we’ll ask for a
1-minute Loom video : tell us who you are and why you’re excited about Wordware.
15-min intro call Quick check to align on location, motivation, and logistics. If it’s a go, we move fast from here.
45-minute technical interview You’ll build a small full-stack app. We’re looking for fluency, speed, and product sense.
System design interview A deep dive into how you think and architect systems. We’ll walk through a real Wordware problem together.
Final conversation Quick vibe check, answer your questions, and scope out the work trial.
Work trial Paid, in-person, and real — typically 3 days to 2 weeks. You’ll work on something meaningful with us.
#J-18808-Ljbffr