Frontier Agent Engineering Manager, Enterprise

Scale AI · San Francisco, CA; New York, NY · Enterprise Engineering · listed January 27, 2026

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The shape of it

Seniority

Manager

Experience asked

3–5 years

Where

Not stated

Stated pay

$252,000 – $315,000 USD

Requirements listed

Length

1,320 words

In the posting’s own words

As a Forward Deployed AI Engineering Manager 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, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

What it asks for · 5

5+ years of software engineering experience with 3+ yrs of Management 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

Also a plus

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)

Tools and skills named

Models & research

Machine learning4×
Prompt engineering3×
Fine-tuning
LLM

Cloud & infra

AWS
Azure
CI/CD
Docker
GCP
Kubernetes
Terraform

Data

Data pipelines2×
Experimentation2×
ETL

Security & compliance

Security2×
GDPR
HIPAA
SOC 2

Languages

Python

Ways of working

Testing

Words the posting leans on

customer22×
data17×
agent13×
engineering10×
technical9×
experience8×
systems8×
model6×
customer data5×
enterprise5×
infrastructure5×
pipelines5×
solutions5×
deep4×
integration4×
platform4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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