Forward Deployed AI Engineering Manager, Enterprise

About This Role

As a Forward Deployed AI Engineering Manager on our Enterprise team, you will be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You will lead a team to understand client challenges, architect specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

Responsibilities

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries
• Develop production-grade AI agents tailored to customer use cases across domains
• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team collaborating with customer data scientists, ML engineers, and software developers
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases

Requirements

• 5+ years of software engineering experience
• 2+ years of Management experience
• Strong fundamentals in data structures, algorithms, and system design
• Production Python expertise
• Experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure)
• Experience with modern data infrastructure
• Strong problem-solving skills
• Excellent communication skills

Qualifications

• 5+ years of software engineering experience with 2+ years of Management experience

Nice to Have

• Deep understanding of LLMs, prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects
• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Skills

* Required skills

Benefits