1 year ago
San Francisco, CA, USAMid Level
Responsibilities
- Design and manage cloud infrastructure, primarily on AWS, using infrastructure-as-code.
- Establish CI/CD pipelines and engineering practices using GitHub Actions, Docker, and Kubernetes.
- Build and maintain scalable data ingestion and orchestration pipelines for ML and product analytics.
- Administer and optimize PostgreSQL databases and analytical warehouse workloads, including pgvector-based embeddings.
- Collaborate with AI/ML engineers to deploy and monitor LLM and matching models for inference, evaluation, and retraining.
- Implement logging, metrics, traces, and alerts across backend services, data jobs, and model endpoints.
- Drive reliability, performance, and scalability across web, mobile, voice, agentic, and batch systems.
- Partner with product, design, and ML teams to align infrastructure with user and business needs.
Requirements
- 4+ years of experience in infrastructure, platform, or data engineering, preferably in startup or high-growth environments.
- Strong proficiency in Python, TypeScript, and scripting with Bash and YAML.
- Deep understanding of cloud architecture, including AWS, GCP, or similar platforms, and infrastructure-as-code using Terraform, Pulumi, or CloudFormation.
- Experience with containerization and orchestration using Docker, Kubernetes, and ECS.
- Proven ability to design and operate data pipelines and distributed systems.
- Experience with PostgreSQL, data modeling, and schema design for real-time and analytical workloads; pgvector or embeddings experience is preferred.
- Familiarity with ML/AI workflows such as model training, inference, monitoring, and feature stores is preferred.
- Knowledge of observability, cost optimization, and security fundamentals.
- Collaborative mindset, strong ownership, and a bias toward shipping working systems quickly.
Benefits
- Opportunity to work directly with the founding team and help establish architecture, engineering culture, and best practices.
- Early-stage ownership over the technical foundation of an AI-driven product.
- The role involves building from a blank slate and shaping how the product scales, performs, and evolves.
Tech Stack
Categories
Data EngineeringDevOps
About Pear VC
Pear VC is an early-stage venture capital partnership that invests at pre-seed and seed, pairing capital with hands-on support, mentorship, and programs like its PearX accelerator for founding teams. Founded in 2013 and headquartered in Menlo Park, California, it backs software and technology startups across categories. Its portfolio includes companies that reached the public markets, such as DoorDash and Guardant Health.