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About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI ...

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Selected role

Forward Deployed AI Engineer, Enterprise

Scale AI

$179k Senior Full-time

About Scale AI
Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

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
Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
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, fine-tuning, embeddings, and RAG architectures
Experience building and deploying AI agents or autonomous systems in production
Background in machine learning, with hands-on experience training or fine-tuning models
Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
Knowledge of vector databases and semantic search systems
Previous work in a forward deployed, field engineering, or technical account management role
Domain expertise in verticals like finance, healthcare, government, or manufacturing
Contributions to open-source AI/ML projects

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$179,400—$224,250 USD

PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's
Know Your Rights poster
for additional information.
We comply with the United States Department of Labor's
Pay Transparency provision
.
**PLEASE NOTE:*
We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.*

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