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Scale AIScale AI

Forward Deployed AI Engineer, Enterprise

Hands-on Forward Deployed AI Engineer building and deploying custom AI agents, integrations, and RAG systems for enterprise customers. Requires 4+ years of Python/ML engineering experience and strong 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

  • 4+ 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

Agent Development Wiz

  • 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

Infrastructure Guru

  • 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)

Customer Product Whisperer

  • 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

Benefits

  • Comprehensive health, dental and vision coverage
  • Retirement benefits
  • Learning and development stipend
  • Generous PTO
  • Commuter stipend (may be eligible)
  • Equity compensation (subject to Board approval)

Skills

Python, LangChain, Llamaindex, Huggingface, OpenAI API, AWS, GCP, Azure, Docker, Kubernetes, Terraform, RAG, LLMs, Vector Databases, CI/CD

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