Member of Technical Staff, Infra

Department: Engineering

Location: San Francisco

Compensation: $180K – $275K • Offers Equity

Employment Type: FullTime

About Pepr AI

We are building the AI Operator for growth to replace the traditional ad agencies. We apply the quant rigor of high-frequency trading to optimize ad spend, delivering 20-50% upside in spend efficiency. We are managing spend for global category leaders like Cider and Cupshe with a clear path to managing billions of dollars. We are backed by Quiet Capital and are looking for early engineers.

The Role

We are looking for a Backend Engineer to build the bedrock of our autonomous system and champion our internal Developer Experience.

You are the architect of reliability and the multiplier of our engineering velocity. While our algorithms team designs the trading strategies, you ensure the engine runs without interruption. Your role is to operationalize our ML pipelines, manage complex deployments across fragmented client environments and build the paved road that allows our team to ship complex systems safely.

Beyond keeping production flawless, we want our engineering team to be the fastest and most efficient in the world. You will lead our DevEx initiatives by building, evaluating, and integrating cutting-edge AI tooling.

We are looking for the adult in the room – a responsible engineer with 6-8+ years of experience who can foresee failure modes before they happen while simultaneously pushing the boundaries of how a modern, AI-native engineering team operates. You will be the guardian of production quality and the visionary keeping our internal tooling at the frontier of software development.

What You'll Do

• Operationalize the Quant Engine: Transform experimental ML models into resilient production services. You will build the training, inference and retraining pipelines that ensure our models are always fresh and performant.

• Build the Event-Driven Backbone: Architect the scheduling and event-driven triggers that power our high-frequency control loops. You will manage the message queues (e.g., Kafka, SQS) and orchestration layers (e.g., Airflow, Dagster) that coordinate data flow between our context, decision and execution.

• Pioneer AI-Native Developer Experience: You view internal engineers as your customers. You will integrate and build cutting-edge AI tooling such as custom agents, automated AI code reviews and hosted sandboxes to accelerate engineering velocity.

• Architect Multi-Environment Deployments: Design and manage the infrastructure to deploy our decision engine into diverse environments including our own cloud and private client VPCs. You will solve the complex challenges of managing software lifecycles across isolated and secure instances.

• Guardian of Reliability: Unexpected issues inevitably arise. You will own system health, setting up comprehensive observability (monitoring, logging and tracing) and acting as the primary troubleshooter when things break.

Who You Are

• A Senior Operator: You have 6-8+ years of experience in ML Platform, Developer Experience or Infrastructure Software Engineering roles. You have seen how systems break at scale and know how to design them to survive.

• Distributed Systems Native: You are comfortable working with complexity at scale. You understand the challenges of data consistency, concurrency and latency in distributed environments.

• Architect of Reliability: You prioritize system health and visibility. You build the observability and automation required to run critical workloads in production, ensuring that complex deployments remain stable even as they scale across diverse environments.

• Platform Mindset: You focus on building the paved road that maximizes engineering velocity without sacrificing reliability. You want to make it virtually impossible for your teammates to ship bad code.

• DevEx & AI Tooling Advocate: You actively experiment with the latest AI coding tools (Claude Code, Codex, OpenCode and Cursor) and agentic workflows, and you have a strong vision for how AI can automate the software development lifecycle.

Bonus Points

• MLOps Tooling: Experience with feature stores, model registries and tools like Ray, MLflow or Kubeflow.

• Client VPC / On-Prem Experience: Experience deploying software into customer-controlled environments (AWS/GCP/Azure).

• AI-Native DevEx Implementation: Experience integrating AI tools into your workflows for work or side projects. Familiarity with parallel workflows, automated code review and verification with LLMs.

• Security First: Experience with SOC2 compliance, IAM policies and securing sensitive financial data.

Compensation & Benefits

• Salary: $180,000 – $275,000

• Equity: Significant equity package

• Food: Daily lunch and (optional) dinner

• Relocation: Relocation support for candidates moving to the Bay Area

• Benefits: Comprehensive health, dental, vision and unlimited PTO