Jobs
Compensation
$179,400 - $224,250
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Unlimited PTO
•Learning Budget
•Commuter Benefits
•Healthcare
•401k
•Equity
•Unlimited Pto
•Learning
•Commuter
Required Skills
Python
Software engineering
System design
Cloud platforms
Data infrastructure
Problem-solving
Communication
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
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Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
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Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
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Deploy and configure AI models and agents within customer security and compliance boundaries
AI Agent Development
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Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
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Architect multi-agent systems that orchestrate between different models, tools, and data sources
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Implement evaluation frameworks to measure agent performance and iterate toward business objectives
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Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement
Prompt Engineering & Optimization
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Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
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Build and maintain prompt libraries, templates, and best practices for customer use cases
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Conduct systematic prompt experimentation and A/B testing to improve model outputs
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Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate
Technical Leadership & Collaboration
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Serve as the primary technical point of contact for strategic enterprise accounts
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Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
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Provide technical training and knowledge transfer to customer teams
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Work closely with Scale's product and engineering teams to translate customer needs into product improvements
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Document technical architectures, integration patterns, and best practices
Problem Solving & Innovation
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Debug complex technical issues across the entire stack, from data pipelines to model outputs
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Rapidly prototype solutions to unblock customers and prove out new use cases
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Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
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Identify opportunities for productization based on common customer patterns
Required Qualifications
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4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
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Production Python expertise with experience in modern ML/AI frameworks (e.g., Lang Chain, Llama Index, Hugging Face, OpenAI API)
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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
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Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
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Experience building and deploying AI agents or autonomous systems in production
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Knowledge of vector databases and semantic search systems
-
Contributions to open-source AI/ML projects
Infrastructure Guru
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Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
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Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
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Previous work in a devops, platform, or infra role
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Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
Customer Product Whisperer
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Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
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Domain expertise in verticals like finance, healthcare, government, or manufacturing
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Experience with technical enablement or teaching programs
Sample Projects
The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.
Deep Research for Due Diligence
For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.
Churn Prediction
Working with a Tel Co organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.
Data Extraction Voice Agent
We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.
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 accommodations@scale.com. 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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About Scale AI

Scale AI
Series CAccelerate the development of AI applications.
501-1,000
Employees
San Francisco
Headquarters
$7.3B
Valuation
Reviews
3.5
2 reviews
Work Life Balance
1.5
Compensation
3.5
Culture
2.0
Career
3.0
Management
1.5
25%
Recommend to a Friend
Pros
Famous in tech world
Good for career transitions
Offers equity after 1 year
Cons
Extremely long working hours (80+ per week)
Unprofessional recruiting process
Poor communication during hiring
Salary Ranges
0 data points
Junior/L3
L3
Junior/L3 · Data Scientist L3
0 reports
$123,049
total / year
Base
-
Stock
-
Bonus
-
$104,592
$141,506
Interview Experience
5 interviews
Difficulty
3.2
/ 5
Duration
14-28 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 60%
Negative 20%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Final Round
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
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