Founding AI Platform Engineer – MLOps, Backend

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and sustain the infrastructure and tools that facilitate the training, evaluation, deployment, and monitoring of ML models and GenAI services.

• Take ownership of production services, APIs, and pipelines that drive recommendations, agent workflows, and integrations for customers.

• Enhance CI/CD processes, testing, release workflows, rollback procedures, and environment management.

• Establish observability metrics for service health, model behavior, agent quality, latency, cost, and potential failure modes.

• Create reproducibility and lifecycle practices for models, prompts, datasets, configurations, and releases.

• Support the infrastructure for experimentation and measurement to ensure product and ML changes can be assessed thoroughly.

• Enhance reliability, scalability, security, performance, and cost-effectiveness throughout the stack.

• Diagnose production issues from start to finish and transform recurring challenges into sustainable engineering enhancements.

• Contribute to defining the platform and engineering standards that the company will depend on as it expands.

⛳️ Requirements

• Solid software engineering experience with a background in building and operating production systems.

• Familiarity with backend services, cloud infrastructure, CI/CD, testing, observability, and automation.

• Proficient in Python with the ability to work seamlessly across services, tools, infrastructure, and operational workflows.

• Good decision-making skills regarding reliability, performance, maintainability, and cost considerations.

• Capability to collaborate effectively with ML and product teams, driving ambiguous tasks to completion.

• Strong sense of ownership, meticulous attention to detail, and a tendency to simplify and strengthen systems.

• Experience with MLOps workflows for model training, evaluation, deployment, and monitoring is a plus.

• Experience in serving ML models or LLM applications in a production environment is advantageous.

• Background in experimentation platforms, event pipelines, analytics instrumentation, or feature delivery systems is a plus.

• Familiarity with agent evaluation, prompt versioning, retrieval/search infrastructure, or vector-backed systems is beneficial.

• Experience in supporting customer-facing APIs or SaaS platform infrastructure is a plus.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work opportunities.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive company culture.