Staff AI Engineer

Join to apply for the Staff AI Engineer (Orchestration) role at Heidi . About Heidi Heidi is building an AI Care Partner that supports clinicians every step of the way, from documentation to delivery of care. We exist to double healthcare’s capacity while keeping care deeply human. In 18 months, Heidi has returned more than 18 million hours to clinicians and supported over 73 million patient visits. Today, more than two million patient visits each week are powered by Heidi across 116 countries and over 110 languages. Founded by clinicians, Heidi brings together clinicians, engineers, designers, scientists, creatives, and mathematicians to strengthen the human connection at the heart of healthcare. Backed by nearly $100 million in total funding, Heidi is expanding across the USA, UK, Canada, and Europe, partnering with major health systems such as the NHS, Beth Israel Lahey Health, MaineGeneral, and Monash Health, among others. The Role You will operate as a Staff+ AI scientist/engineer on the Orchestration team. You will own the design and delivery of a clinician‑grade retrieval and question‑answering stack across data ingestion, indexing, ranking, grounding, and safe deployment. You will set technical direction, establish quality bars, and lead cross‑functional execution with engineering, product, and clinical experts. You will move between research and production, turning prototypes into reliable services with clear SLAs, traceable outputs, and unit/acceptance metrics that matter in clinical contexts. Responsibilities Define the end‑to‑end architecture for literature and guideline ingestion, normalization, metadata extraction, de‑duplication, and versioning. Build hybrid search and retrieval: lexical + vector + re‑ranking, with tight latency budgets and cost controls. Design grounding and answer synthesis that cite sources, preserve provenance, and expose confidence and abstention. Lead model work across prompting, fine‑tuning, distillation, and tool use to improve faithfulness, coverage, and utility. Stand up gold‑standard evaluation: offline IR metrics (nDCG, MAP, recall), factuality/faithfulness audits, and human review with adjudication. Run online experiments at scale. Define guardrails, KPIs, and ship A/Bs to measure impact on clinician workflows. Productionize services with observability, tracing, canaries, rollbacks, and incident playbooks. Set data governance for medical content: access control, PHI handling, audit logs, and retention policies. Partner with clinicians to define intents, schemas, and acceptance criteria. Convert ambiguous questions into testable specs. Coach engineers and scientists. Raise the technical bar through design docs, reviews, and reusable components. Qualifications Staff‑level track record shipping search, NLP, or LLM systems that serve real users at scale. Mastery of Python and SQL. Strong software engineering fundamentals, testing strategy, and API/service design. Depth in modern IR/NLP: embeddings, ANN indexes, re‑rankers, retrieval‑augmented generation, and prompt/program synthesis. Experience building data pipelines: parsing PDFs/HTML, OCR when needed, metadata extraction, and content hashing/versioning. Familiarity with PyTorch, plus distributed training/inference patterns. MLOps and reliability: containers, Kubernetes, feature/model registries, experiment tracking, monitoring, and alerting. Evidence of rigorous evaluation design: offline metrics, human‑in‑the‑loop judging, power analysis for online tests. Clear thinking on safety: hallucination controls, calibration, abstention, red‑teaming, and privacy/security by design. Ability to lead cross‑functional initiatives and make crisp decisions with incomplete information. Bonus Search relevance expertise for long‑form, citation‑heavy domains. Knowledge of biomedical ontologies and standards (e.g., SNOMED CT, UMLS, ICD, RxNorm, FHIR). Prior work with literature and guideline corpora, de‑duplication, and document lineage tracking. Experience with hybrid retrieval stacks (e.g., BM25 + ANN) and learned re‑rankers. Familiarity with clinical evaluation methods, EBM hierarchies, and annotation workflows. Strong cost‑performance tuning for LLM inference, caching, and batching in production. Benefits Flexible hybrid working environment, with 3 days in the office. Additional paid day off for your birthday and wellness days. Special corporate rates at Anytime Fitness in Melbourne, Sydney tbc. A generous personal development budget of $500 per annum. Learn from some of the best engineers and creatives, joining a diverse team. Become an owner, with shares (equity) in the company; if Heidi wins, we all win. The rare chance to create a global impact as you immerse yourself in one of Australia’s leading healthtech startups. Opportunity to fast track your startup career if you have an impact quickly. Job Details Seniority level: Mid‑Senior levelEmployment type: Full‑timeJob function: Engineering and Information TechnologyIndustries: Software Development #J-18808-Ljbffr