What you will do
- Lead architecture, design, and development end to end.
- Integrate backend services with AI / ML pipelines, ensuring data consistency and system performance.
- Collaborate closely with ML and data engineers to deploy, iterate, and monitor AI-powered features.
- Design and maintain robust, scalable, systems capable of handling high traffic.
- Ensure observability, monitoring, performance tuning, and automated recovery mechanisms are in place.
- Own CI/CD pipelines and IaC (Terraform, CloudFormation, etc.) across cloud environments.
What should your qualifications be?
- 8+ years of experience building and scaling production Full-Stack Systems
- Expert proficiency in Python and frameworks like Django and/or FastAPI.
- Strong proficiency in Javascript / Typescript with modern frameworks like ReactJs
- Exposure to AI/ML or data-driven products (e.g. recommendation systems, search, classification)
- Deep knowledge of API design (REST / GraphQL) and databases (PostgreSQL, Redis, or similar).
- Proficiency with cloud infrastructure (AWS preferred) and infrastructure-as-code tools (Terraform, etc.).
- Strong foundation in scalability, fault tolerance, performance tuning, and observability.
- Excellent communication and documentation skills, able to explain complex concepts clearly.
- Comfort working autonomously and making high-impact technical decisions in dynamic environments.
- Tech Expertise
- Programming Languages: Python, Typescript or Javascript.
- Frameworks (two or more): Django, Flask, FastAPI, Celery, ReactJs, NextJs.
- APIs (one or more): GraphQL, Rest API.
- Data storage (one or more): Postgresql, MySQL, AWS RDS
- Cloud & Infrastructure: AWS (preferred) including Lambda, ECS, S3, CloudFront,SQS.
- IaC / Deployment (two or more): Terraform, GitLab CI, GitHub Actions, CircleCI, Jenkins, or similar CI/CD tools.
- Knowledge of performance testing frameworks (two or more): Pytest, Jest, React Testing Library, or equivalent performance and reliability testing frameworks.
- Containerization & Observability (one or more): Docker, Kubernetes, monitoring tools like Datadog, Prometheus, or Grafana.
- Deployment through (one or more): Gitlab CI, Github Actions, Circle CI, Travis CI, Jenkins
- Startup or small-team experience (versus only large organizations).
- Experience integrating or serving AI/ML models in production environments.
- Familiarity with AI/ML ecosystems (e.g. OpenAI, Hugging Face, LangChain).
- Exposure to backend data and infrastructure scaling for AI inference.
- Open-source contributions or personal technical projects.
- Ability to work across multiple cloud environments (AWS preferred).
Compensation
- Competitive compensation
- Remote first work environment
- Laptop subsidy
- Healthcare
- Connectivity
- Wellness
Top Skills
What We Do
Remedy Product Studio works with founders on strategy, execution, and launch of digital products. We collaborate with Seed to Series C companies across healthcare, data, and finance/commerce technology. We have been a long-term partner to companies including ClassPass, HealthReveal, H1 Insights, Sommsation, Ash, and Caraway Health. Partners are typically with us for 3 years, and we engage our venture network to guide them through an average of 2 fundraises, helping them secure investors like Google Ventures, Greycroft, and Serena Ventures. We work closely with investors to fill out rounds and invest in select partners in the form of sweat equity. So, what does a Remedy partnership look like? - Each Remedy team works exclusively with a single partner to synthesize company objectives, create a roadmap, and then deliver a product. - With our unique flavor of agile methodology, our product-led teams distill a partner’s broad vision into a lean scope that can be delivered and tested in a short time frame. - Our cross-functional teams work on product management, full stack and data engineering, DevOps, architecture, QA, and UX/UI design. Throughout a partnership, we gather product metrics to inform long-term technology and business strategy.
