S

Scale AI

Supplies AI training data and builds AI apps

Forward Deployed AI Engineering Manager - Enterprise

Engineering LeadershipUpdated on Nov 7
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 5 years of software engineering experience and at least 3 years of management experience, with strong fundamentals in data structures, algorithms, and system design.
  • Production-level Python expertise and experience with modern machine learning and artificial intelligence frameworks such as LangChain, LlamaIndex, Hugging Face, and the OpenAI API.
  • Experience with cloud platforms such as AWS, GCP, or Azure, and modern data infrastructure.
  • Ability to navigate ambiguous requirements and rapidly iterate toward solutions.
  • Ability to explain complex technical concepts to technical and non-technical audiences.

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, including cloud platforms, data warehouses, and internal APIs.
  • Build 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, including customer support, data analysis, content generation, and workflow automation.
  • Architect multi-agent systems that coordinate 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.
  • Create 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 retrieval-augmented generation systems and fine-tuning pipelines where appropriate.
  • Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts.
  • Lead a team collaborating with customer data scientists, machine learning engineers, and software developers to ensure smooth integration.
  • Work with Scale's product and engineering teams to translate customer needs into product improvements.
  • Document technical architectures, integration patterns, and best practices.
  • Debug complex technical issues across the stack, from data pipelines to model outputs.
  • Rapidly prototype solutions to unblock customers and validate new use cases.
  • Stay current on AI and machine learning research and tools and apply innovative approaches to customer problems.
  • Identify opportunities for productization based on common customer patterns.

Desired Qualifications

  • Deep understanding of large language models, including prompting techniques, embeddings, and retrieval-augmented generation 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 and machine learning projects.
  • Experience with containerization tools such as Docker and Kubernetes, and continuous integration and continuous delivery pipelines.
  • Experience using Terraform, Bicep, or other infrastructure-as-code tools.
  • Previous experience in a DevOps, platform, or infrastructure role.
  • Familiarity with enterprise security, compliance, and governance requirements, including SOC 2, GDPR, and HIPAA.
  • Ability to work with customers in a technical consulting, solutions engineering, or product engineering role.
  • Domain expertise in finance, healthcare, government, or manufacturing.
  • Experience with technical enablement or teaching programs.

About the Company

Scale AI

Supplies AI training data and builds AI apps

Scale AI supplies the data that AI labs use to train and test their models, and it builds custom AI applications for companies and government agencies such as the Pentagon. It first made its name labeling camera and sensor data for self-driving car companies like Waymo, then worked with OpenAI on InstructGPT, the 2022 forerunner of ChatGPT. Freelancers, some of them doctors and lawyers, write, label, and grade examples through its Outlier platform, and labs pay Scale for this data and for tests of model quality. Clients pay Scale to build AI tools on their own data, and some of those tools run on classified military networks. Alexandr Wang and Lucy Guo founded Scale AI in 2016, and it is based in San Francisco.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$1.6B
Headquarters
San Francisco, CA
Founded
2016

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