Abridge

About the Company

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our Best in KLAS AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most--their patients.

Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.

Listed Jobs

Company Name

Abridge

Job Title

Senior Platform Engineer

Job Description

Job title: Senior Platform Engineer Role Summary: Lead the design, deployment, and scaling of Abridge’s multi‑tenant, multi‑cloud infrastructure. Own the end‑to‑end platform stack—cloud networking, IAM, Kubernetes, databases, streaming, and observability—to deliver high‑velocity, secure, and compliant services for a rapidly expanding engineering organization. Expactations: • 8+ years of software engineering experience, with 3+ years focused on infrastructure‑as‑code in a cloud‑first environment. • Proven ability to architect and operate large‑scale Kubernetes clusters, including upgrades, service mesh, and Helm management. • Hands‑on experience with Terraform/Terragrunt, CI/CD tooling, and cloud security best practices (least‑privilege, scanning, SoC2/HIPAA compliance). • Strong communication skills to evangelize platform practices, mentor engineers, and represent the platform at external events. Key Responsibilities: - Design, build, and maintain cloud infrastructure (VPC, GKE, IAM, storage, pub/sub, databases) using IaC. - Create and scale CI/CD pipelines for both infrastructure and application code (e.g., ArgoCD, Argo Rollouts, Octopus Deploy, Travis CI). - Implement cloud security controls, automated scans, and audit trails; maintain SoC2 and HIPAA compliance. - Develop and maintain service templates, canary release mechanisms, feature flags, and load‑testing frameworks. - Enhance observability: metrics, logs, traces with Grafana, Datadog, Honeycomb; improve runbooks and incident response. - Bridge development and production environments to reduce drift and boost velocity. - Document, train, and evangelize platform solutions internally and to the broader community (conferences, open source). Required Skills: - Proficiency with Google Cloud Platform: Projects, VPC, GKE, IAM, Cloud Build. - Advanced Terraform/Terragrunt and GitOps tooling (ArgoCD, Argo Rollouts). - Kubernetes cluster operation, service mesh (Istio), Helm, and version upgrade strategies. - CI/CD pipeline design for IaC and application code; familiarity with Octopus Deploy, Travis CI. - Observability platforms: Grafana, Datadog, Honeycomb; metrics, logs, traces. - Cloud security: IaC scanning, least‑privilege IAM, compliance frameworks (SoC2, HIPAA). - Backend development in Python, Go, Node, or Rust. Required Education & Certifications: - Not specified. ---

San francisco, United states

Hybrid

Senior

26-12-2025

Company Name

Abridge

Job Title

Software Engineer, Gen AI Platform

Job Description

Job Title: Software Engineer, Gen AI Platform Role Summary: Design, build, and maintain a scalable, secure runtime for generative AI agents that orchestrate large language model (LLM) workflows, tool calling, and structured outputs in a medical context. Expectations: Deliver production‑ready, high‑performance code; ensure reliability, observability, and security; collaborate with research, product, and clinical teams; own end‑to‑end agent pipeline from prototype to deployment; actively improve agent reliability through evaluation and metrics. Key Responsibilities: - Architect and implement a highly available agent orchestration engine (state, memory, scheduling, cost/latency optimization). - Build sandboxed execution for agent actions and code; optimize cold‑start, isolation, and observability. - Create unified interfaces for multiple LLM sizes/providers; integrate open‑tool ecosystems (e.g., MCP‑style connectors). - Develop online/offline evaluation infrastructure (A/B tests, safety checks, regression gates) to continuously improve agent robustness. - Partner with research to transition new agent capabilities from prototype to production. Required Skills: - Proven experience building agent applications with tool‑calling, context engineering, and connector integrations. - Proficiency with LLM APIs, prompting strategies, and orchestration patterns (LangChain, LlamaIndex, or custom pipelines). - Knowledge of retrieval systems (semantic/lexical retrieval, vector DBs, efficient kNN), function calling, and agentic workflows. - Strong coding in Python, Java, or Go; service design, API development, and data modeling for high‑throughput systems. - Working knowledge of containers, Kubernetes, metrics, tracing, on‑call, and incident response. - Excellent communication and cross‑functional collaboration skills. Required Education & Certifications: - Bachelor’s or higher in Computer Science, Software Engineering, or related field. - Relevant certifications (e.g., Kubernetes, cloud architecture) preferable but not mandatory.

San francisco, United states

Hybrid

07-02-2026

Company Name

Abridge

Job Title

Machine Learning Scientist (All Levels)

Job Description

**Job Title**: Machine Learning Scientist **Role Summary**: Develop and advance AI/ML solutions for healthcare applications, including medical conversation summarization, evidence extraction, and outcome prediction. Innovate to resolve complex NLP challenges while publishing research and deploying models into production systems. **Expectations**: Proven research track record via publications, academic qualifications, and real-world deployments. Demonstrated ability to translate ambiguous healthcare problems into actionable technical solutions. **Key Responsibilities**: - Advance state-of-the-art methods in medical NLP, including conversation summarization, evidence extraction, and evaluation techniques. - Design, prototype, and deploy machine learning models into production. - Collaborate on defining high-impact research problems and validating effectiveness. - Publish original research in peer-reviewed AI conferences and journals. - Incorporate clinician feedback to refine models and drive iterative improvements. **Required Skills**: - Expertise in natural language processing (NLP), deep learning frameworks (PyTorch, Jax, TensorFlow), and statistical analysis of observational/experimental data. - High-impact publications in top AI/ML conferences (e.g., NeurIPS, ICML, ACL, MLHC). - Experience with multi-GPU training and production ML deployment pipelines. - Open-source contributions or deployed systems demonstrating real-world impact. **Required Education & Certifications**: - MS or PhD in Computer Science, Mathematics, Electrical Engineering, or equivalent experience with strong research accomplishments.

San francisco, United states

Hybrid

07-02-2026