S
Scale AI
Senior Frontier Agent Engineering Manager (Enterprise)
Skills
Google Cloud PlatformDockerPythonData AnalysisMachine LearningAIAWSKubernetesNo-code AutomationsCustomer SupportComplianceTerraformAzure
19 days ago
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Important information
Contract type:
Permanent
Salary:
$216,200 – $270,250 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
8 October 2026
What they need
- 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
- This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems
- You’ll work directly with customer engineering teams to integrate AI into their critical workflows
- 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
- 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
- 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
- Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
- Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
- Work closely 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 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
Benefits
- Health & Wellbeing: Our holistic approach to supporting Scaliens includes comprehensive health coverage, dental and vision insurance, mental healthcare services, and more. PTO policies and accommodating schedules ensure you’ll get time off when you need it to relax and recharge. Note that our offerings may vary by region as we strive to respond to the unique needs of Scaliens around the globe.
- Personal & Career Growth: Continuously learn and grow through annual learning & development stipend, attending leadership breakfasts, manager training, speaker series, and joining an ERG.
- Building Scale Community: We welcome guests to our offices, and you can expect to see Scalien families and friends around. Join local happy hours, and accept invites to game nights, book clubs, and many other employee-led community events.
- Parental Support: Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.- 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)
- Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences
- 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
- Domain expertise in verticals like finance, healthcare, government, or manufacturing
- Experience with technical enablement or teaching programs
- Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
- Previous work in a devops, platform, or infra role
- Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
- Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
- Contributions to open-source AI/ML projects
- Experience building and deploying AI agents or autonomous systems in production
- Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
- Knowledge of vector databases and semantic search systems
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