About Chestnut
Chestnut is constructing the primary AI-native working system for insurance coverage distribution by reworking how the $1T+ insurance coverage trade allocates its largest spend: gross sales and distribution.
Backed by a16z, we’re changing legacy programs with a contemporary, versatile platform that helps carriers automate advanced workflows, optimize each distribution greenback, and unlock new progress. We’ve got main insurers underneath contract, and early adopters are increasing.
This can be a generational platform shift. Latest advances in agentic AI make it doable to automate what was as soon as handbook and error-prone. We’ve spent years constructing the information mannequin and context layer required to make this actual, and now we’re scaling with urgency.
At Chestnut, we function with the assumption that small, high-context groups working with best-in-class instruments and colleagues can obtain outsized outcomes. We embody what it means to be AI-lean: chasing 10x productiveness good points that enable us to scale affect past our headcount.
For those who’re excited to modernize the infrastructure of considered one of America’s most important industries, we’d love to fulfill you. Whether or not shaping core product experiences or laying the groundwork for clever automation, your work will speed up a once-in-a-generation transformation.
Engineering at Chestnut
We’re constructing the fashionable infrastructure for AI-driven insurance coverage operations. Meaning well-structured knowledge fashions, real-time occasion pipelines, clear APIs, and usable instruments that assist people and brokers working in parallel.
As a Software program Engineer at Chestnut, you’ll be part of a high-agency, cross-functional staff targeted on delivering impactful options quick. You’ll work throughout the stack, contribute to system design, and assist form the technical tradition as we develop.
Why This Function Exists
We’re hiring a junior Ahead Deployed Engineer to assist us deliver our product to life inside buyer environments. You’ll work on actual issues, in manufacturing, with actual customers—typically inside weeks of becoming a member of. For those who’re the type of engineer who desires to know the enterprise, discuss to clients, and ship scrappy-but-scalable options, this position provides you the playground and the strain.
What You’ll Do
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Implement our platform for brand spanking new clients—mapping knowledge, constructing workflows, writing glue code
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Write scripts, API calls, and inside instruments to unblock onboarding and drive adoption
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Help onboarding efforts by translating messy buyer knowledge into structured, usable codecs
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Work alongside senior engineers and options of us to show buyer wants into delivered outcomes
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Determine gaps in present tooling and counsel enhancements to our AI and deployment stack
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Be taught a ton. This can be a high-context, high-velocity position, and we’ll put money into serving to you develop
What We’re Trying For
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0–2 years expertise, with strong coding fundamentals (Python, Go, or TypeScript superb)
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Curious, resourceful, and biased towards motion—you’re not afraid to determine issues out
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Curiosity in utilized AI—whether or not it’s workflow automation, knowledge enrichment, or retrieval-augmented technology
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Robust communicator who desires to know each the tech and the enterprise
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Snug with ambiguity, desirous to be taught from others, and motivated to personal actual issues
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Willingness to journey as much as 25% for high-leverage, in-person work
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Bonus: expertise with LLMs, open-source AI instruments, or aspect tasks that shipped
Why You Would possibly Be a Match
You need to do extra than simply write code—you need to construct issues individuals really use. You’re enthusiastic about AI, however you care extra about what it may possibly do than the way it’s marketed. You need to be near the client, near the product, and within the room as selections get made. We’ll provide you with actual scope, actual mentorship, and an actual path to develop.
Our Stack
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Languages: Go, TypeScript
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Frontend: React
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Orchestration: Temporal, Dagster
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Infra: AWS, K8s, ArgoCD
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Information: Postgres, Dynamo, Snowflake
Advantages
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Aggressive wage and fairness, with 10 12 months train window for inventory choices
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Distant-first tradition constructed on belief, autonomy, and excessive efficiency
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Staff offsites for all of us to bond
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Take what you want trip coverage
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High notch well being, dental, and imaginative and prescient insurance coverage sponsored by us