# Forward Deployed AI Engineering Manager, Enterprise

**Company:** [Scale AI](https://hotfix.jobs/companies/scale-ai)
**Location:** San Francisco, CA, New York, NY
**Role:** Engineering Management
**Salary:** $216k – $270k/yr
**Experience:** 5+ years
**Skills:** Python, LangChain, Llamaindex, Huggingface, OpenAI API, AWS, GCP, Azure, Docker, Kubernetes
**Posted:** 2026-02-12

> Lead a team as technical bridge for enterprise customers, architecting and deploying custom AI agents, integrations, and prompt engineering solutions into production environments. Requires 5+ years software engineering with 2+ years management, Python expertise, and cloud experience.

## Job Description

## Key Responsibilities

### Customer Integration & Deployment
- Partner with enterprise customers to understand 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

### Leadership & Collaboration
- Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
- Lead a team collaborating with customer data scientists, ML engineers, and software developers
- 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
- Identify opportunities for productization based on common customer patterns

## Required Qualifications
- **5+ years of software engineering experience** with **2+ years of management experience** and 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
- Excellent communication skills

## Preferred Qualifications

**Agent Development**
- 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

**Infrastructure**
- Experience with containerization (**Docker**, **Kubernetes**) and CI/CD pipelines
- Experience using **Terraform**, Bicep, or other IaC tools
- Previous work in a devops, platform, or infra role
- Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

**Customer Product**
- Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
- Domain expertise in verticals like finance, healthcare, government, or manufacturing
- Experience with technical enablement or teaching programs

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