WHAT YOU’LL DO
Lead the design and implementation of Harvey's Model Infrastructure platform.
Build systems to ensure high availability, low latency, and operational excellence for AI inference.
Design and improve Harvey's Unified Model Controller (UMC) and Model Selector platform to automatically detect model degradations and intelligently route traffic based on reliability, latency, quality, compliance, and cost.
Develop systems for model provisioning, capacity management, failover, and traffic engineering across multiple AI providers.
Integrate new model providers and maintain provider APIs and SDKs, enabling Harvey to rapidly adopt emerging frontier models.
Improve observability through health dashboards, alerting, token usage analytics, cost reporting, and end-to-end telemetry.
Partner with Product Engineering to support model launches, experimentation, and proactive monitoring of production AI workloads.
Drive infrastructure efficiency through capacity planning, utilization optimization, and cost visibility.
Collaborate with AI Research to build the infrastructure foundation for future model evaluation, training, and deployment.
Lead cross-functional technical initiatives and mentor engineers across the organization.
WHAT YOU’LL BUILD
Model Reliability & Operations
Model health monitoring
Automated failover and recovery
Capacity provisioning
Operational tooling and incident automation
Unified Model Controller (UMC)
Policy-based model routing
Intelligent Model Selector
Model health monitoring
Traffic management
Reliability and latency optimization
Provider Platform
Multi-provider architecture
API and SDK integrations
OpenAI, Anthropic, Azure OpenAI, Fireworks, Baseten, and future providers
Rapid adoption of new frontier models
Observability & Cost Platform
Token usage analytics
Cost attribution
Latency and reliability dashboards
Capacity forecasting
Utilization optimization
AI Platform Foundation
Infrastructure supporting model evaluation
Model deployment and operations
Future model training platform
Agent infrastructure and CcaaS
WHAT YOU HAVE
10+ years of software engineering experience building large-scale distributed systems.
Experience designing and operating highly available production services.
Strong programming skills in Go, Java, Python, Rust, or C++.
Deep understanding of distributed systems, cloud infrastructure, networking, and observability.
Experience leading technical projects across multiple engineering teams.
Ability to balance long-term architecture with pragmatic execution.
Strong communication and collaboration skills.
Passion for building foundational platforms that enable other engineering teams.
NICE TO HAVE
Experience with AI infrastructure, LLM serving, or machine learning platforms.
Experience with model routing, inference gateways, or policy-based serving systems.
Experience working with OpenAI, Anthropic, Azure OpenAI, Fireworks, Baseten, or open-source LLMs.
Experience with Kubernetes, cloud infrastructure, and service mesh technologies.
Experience with large-scale observability and SRE best practices.
Experience with data infrastructure technologies such as Kafka, Spark, Flink, Airflow, or Iceberg.
Familiarity with GPU infrastructure or model training platforms.
COMPENSATION
$236,000 - $340,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
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Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
