Jobs at Accrete AI

Build end-to-end frontend and backend features for an AI platform: design UIs for model interaction, develop scalable APIs and services, integrate ML models, improve reliability and performance, and own projects from concept to deployment.

Develop a unified AI platform by designing and building scalable applications, improving platform performance, and collaborating with ML engineers.

The Accountant I will manage daily accounting operations, support month-end closes, perform reconciliations, handle payroll entries, and ensure compliance with financial reporting standards.

The Senior DevOps Engineer leads cloud infrastructure and pipeline management, focusing on automation, CI/CD processes, system performance, and mentoring junior engineers.

Serve as the company's chief legal officer: lead corporate governance, negotiate and manage contracts, direct IP strategy and patent/trade secret protection, advise executives and the board, oversee M&A and licensing, manage outside counsel and legal budgets, ensure compliance with federal procurement, cybersecurity and data privacy regulations, and support crisis management and internal investigations.

Lead Forward Deployed Engineering to scale customer implementations of Accrete's AI platform from discovery to production. Build operating models, delivery standards, staffing plans, and playbooks; manage and mentor teams; partner with Product, Engineering, Research, and customers to ensure secure, reliable, and scalable deployments with measurable impact.

Lead end-to-end technical deployments with strategic customers: scope, design, build, integrate, and stabilize AI-powered full-stack systems. Work directly with customer teams to translate workflows into production-grade solutions, configure AI agents and retrieval pipelines, support rollout and monitoring, and provide product feedback to improve models and platform capabilities. Travel up to 50%.

Build and optimize scalable AI infrastructure and distributed systems for model training and inference. Integrate research into production, improve model efficiency, ensure reliability and security, collaborate with cross-functional teams, and maintain large-scale data pipelines.