Senior Forward Deployed AI Engineer, Enterprise

Hands-on Senior Forward Deployed AI Engineer who partners with enterprise customers to architect, integrate, and deploy custom AI agents and solutions into production environments. Requires 5+ years software engineering experience, strong Python and ML framework expertise, cloud platform experience, and excellent customer-facing technical skills.

About the job

Key Responsibilities

Customer Integration & Deployment

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 (cloud platforms, data warehouses, internal APIs)
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

AI Agent Development

Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
Architect multi-agent systems that orchestrate between different models, tools, and data sources
Implement evaluation frameworks to measure agent performance and iterate toward business objectives
Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
Build and maintain prompt libraries, templates, and best practices for customer use cases
Conduct systematic prompt experimentation and A/B testing to improve model outputs
Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

Serve as the primary technical point of contact for strategic enterprise accounts
Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
Provide technical training and knowledge transfer to customer teams
Work closely with Scale's product and engineering teams to translate customer needs into product improvements
Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

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
Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
Identify opportunities for productization based on common customer patterns

Required Qualifications

5+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Deep understanding of LLMs including 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