# Senior Forward Deployed AI Engineer, Enterprise

**Company:** [Scale AI](https://hotfix.jobs/companies/scale-ai)
**Location:** San Francisco, CA, New York, NY
**Role:** Solutions Architecture
**Salary:** $216k – $270k/yr
**Experience:** 5+ years
**Skills:** Python, LangChain, Llamaindex, Huggingface, OpenAI API, AWS, GCP, Azure, Docker, Kubernetes, Terraform, RAG, LLMs, Vector Databases, CI/CD
**Posted:** 2026-05-16

> Hands-on Senior Forward Deployed AI Engineer who partners with enterprise customers to architect, integrate, and deploy custom AI agents and solutions into production environments. Requires 5+ years software engineering experience, strong Python and ML framework expertise, cloud platform experience, and excellent customer-facing technical skills.

## Job Description

## 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
- 5+ 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
- 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, 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)
- 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

## Compensation & Benefits
- Base salary range: $216,000–$270,000 USD
- Equity compensation
- Comprehensive health, dental, and vision coverage
- Retirement benefits
- Learning and development stipend
- Generous PTO
- Commuter stipend (eligible roles)

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