Build the system of record for how claims get decided.
We're a small team shipping a fine-tuned LLM stack into US payers, Indian TPAs, and the hospital networks that bill them. Every decision the system makes is cited and signed. Help us make it correct, fast, and defensible.
Live inside our first US payers and Indian TPAs for weeks at a time. Translate their ground truth — denial logic, IRDAI quirks, NPPA caps, NABH workflows — into product. The first ten hires here will shape how Adjudo gets adopted.
You
5+ years shipping software with at least 1 year embedded with customers
Comfortable writing production code in Python or TypeScript and SQL
Strong instinct for what to build, what to script, what to throw away
Empathy for non-technical reviewers; you'll sit next to claims officers
Nice to have
Prior life in health insurance, TPA ops, payer claims, or hospital revenue cycle
Experience with HL7/FHIR, X12 837/835, or IRDAI/NABH workflows
Own the inference path end-to-end. We serve fine-tuned LLMs on Lambda H100s, AWS, and customer on-prem (NABH-bound hospitals can't ship PHI to the cloud). You'll run vLLM, optimize prefix caching for chat, push p99 latencies down, and design a deploy story that ships to a payer's VPC and a hospital's air-gapped rack with the same artifact.
You
Ran production inference at scale — vLLM, TensorRT-LLM, SGLang, or similar
Adjudo handles PHI on day one. You'll own HIPAA controls for the US side, IRDAI + DPDP for the India side, and walk us through SOC 2 Type II in year one. The audit trail is signed by construction (HMAC-chained adjudications) — your job is to make sure the rest of the surface is just as defensible.
You
5+ years in security engineering at a health, fintech, or infra company
Hands-on with threat modeling, SAST/DAST, secret hygiene, IAM design
Have led at least one SOC 2 / HIPAA / ISO 27001 audit through to signed report
Read code as well as policy — you can spot a bad RLS policy and a bad DPA clause
Nice to have
Familiarity with PHI handling, BAA workflows, and IRDAI / DPDP requirements
Worked on detection engineering or incident response in regulated industries
Backend Engineer · Health Tech
Remote (US / India) · Mumbai or SF preferred·Full-time
Build the claims engine itself: ingestion, normalization, the policy-clause graph, the adjudication state machine, the audit ledger. You'll integrate with TPA back-offices, payer claim systems, and EHR/HIS feeds. We care more about correctness and explainability than throughput — every byte you process gets cited in a signed decision.
You
5+ years building backend systems in Python / Go / TypeScript
Strong on Postgres, schema design, and event-sourced or append-only data models
Comfortable with FastAPI, async I/O, and writing the test that catches the regression
Domain interest in healthcare — claims, billing codes, policy logic
Own the model — fine-tune, eval, deploy, observe, redo. We've already shipped Qwen2.5-14B fine-tunes that beat GPT-4o on every TPA decision metric. Next: better RAG over policy clauses, faster decoders, drift detection, and a continuous eval loop fed by real reviewer corrections.
You
Trained or fine-tuned LLMs (LoRA / QLoRA / full SFT) on real, messy data
Built rigorous evals — not just accuracy, but calibration, drift, and failure-mode breakdowns