Salary
≈ $8.5k – $23k per year (Estimated)
Location
In office (Bengaluru)
Experience
2+ years exp
First seen by Alion on Oct 22, 2026.
Overview
Company
Impact
Profile match
Thena is a software company that grew from the shift of business customers toward the flexible communication they know from consumer messaging, and it builds systems that turn messy enterprise data into correct, machine-readable output. Its engineers work on long-running data processes that scale to millions of rows, with language models as a reasoning step. The company is headquartered in San Francisco, United States.
Backed by Lightspeed Venture Partners
Responsibilities:
- Build APIs and business logic in NestJS; the service layer that everything else hangs off.
- Write Temporal workflow definitions in TypeScript: durable, long-running processes that stay alive for days across restarts, retries and waits on the outside world.
- Build the React + Vite interface that gives operators visibility into what the system is doing and why.
- Work in Python on the data side Polars and DuckDB over Parquet to transform datasets far too large to hold in memory.
- Wire up Azure infrastructure: blob storage, queues, containerised deploys.
- Write the tests that matter. Output can be perfectly well-formed and still be wrong. Catching that is the interesting part of the job.
Requirements:
- Roughly 2 years of professional engineering, with real shipped work behind you. We care about what you have built, not where.
- Strong TypeScript and comfort in Python. You do not need both at expert level, but you should be genuinely unbothered by moving between them.
- Solid SQL and a working feel for how data is actually shaped in the wild: messy, inconsistent, missing columns.
- You read documentation and source code before asking. When something breaks, your instinct is to find out why rather than to try another thing.
- You write clearly. Much of this job is describing a system precisely to someone who cannot see your screen.
Nice to Have:
- Exposure to workflow engines Temporal, Airflow, Step Functions, or any durable-execution model.
- Anything you have built with LLMs where the output had to be correct rather than merely plausible.
- Columnar data tooling: Polars, DuckDB, Arrow, Parquet.
- Docker, CI, infrastructure-as-code.
Skills
JavaScript, Python, SQL, TypeScript
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