Senior Infrastructure Engineer, Komodo Health

• Engineering Excellence: Proficiency in Python, with deep technical troubleshooting skills and extensive experience building backend APIs and microservices
• Cloud Infrastructure: Expert-level knowledge of AWS core services and the ability to architect scalable solutions from high-level requirements
• Infrastructure as Code & CI/CD: Proficiency in Terraform/Scalr and experience building robust CI/CD pipelines using GitHub Actions
• Networking & Connectivity: Solid understanding of networking fundamentals (subnets, CIDR, VPCs) to ensure secure, global application accessibility
• Big Data Frameworks: Expert with big-data tools and workflow orchestrators such as Snowflake, Databricks, Airflow, Temporal
• AI & Productivity: Ability to leverage AI tools (Gemini, ChatGPT, Cursor) to streamline engineering workflows and enhance personal productivity
• Leadership & Collaboration: A proactive team player with excellent cross-team communication skills and a proven track record of driving complex projects to completion

Desirable

• Komodo aims to build the best healthcare data architecture in the industry. We are rapidly growing and expanding our infrastructure stack and adopting SRE best practices
• You will be joining the Platform team. We build, operate, and constantly improve our infrastructure offerings for 150+ client organizations
• The team achieves our business goals by adopting best infrastructure practices and leveraging 100% automation to scale our product offerings and reduce costs
• You will work with passionate team members across the country, and to accomplish our goal: reduce the burden of disease
• Looking back on your first 12 months at Komodo Health, you will have accomplished…
• Have developed a deep understanding of Platform and Platform customers
• Have built and operated cloud infrastructure (AWS) based on customer requirements
• Have solved any development and deployment challenges around making Platform infrastructure highly reliable, easy to maintain, and cost-effective
• Have participated in the development, execution, and support of the new feature rollout with solution architects, forward-deployed engineers, and customer success teams
• Led the development of improvements to data infrastructure, pipeline automation, codebase quality, and/or data quality
• Designed, architected and/or implemented systems for supporting data processing tasks, like metadata, configuration and/or data pipeline inputs
• Have developed and contributed to existing and new monitoring and alerting systems for Platform infrastructure
• Have hardened infrastructure security including network, storage, user access, etc
• Have responded and solved key customer reported issues in a timely manner
• Participated in an on-call rotation
• Spearheaded the adoption of AI-driven development workflows, integrating LLM-based tools into the SDLC to accelerate feature delivery and reduce mean time to resolution (MTTR)