Base Salary
$252k - $315k/yr
Responsibilities
- Partner with enterprise customers to understand their infrastructure, data pipelines, and business requirements.
- Design and implement integrations between Scale AI’s platform and customer cloud platforms, data warehouses, and internal APIs.
- Build 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 AI agents, multi-agent systems, evaluation frameworks, human-in-the-loop workflows, and feedback mechanisms.
- Create prompt strategies, prompt libraries, templates, experimentation programs, A/B tests, RAG systems, and fine-tuning pipelines.
- Serve as the primary technical contact for strategic enterprise accounts and provide technical training and knowledge transfer.
- Collaborate with customer and Scale AI data scientists, ML engineers, software developers, product teams, and engineering teams.
- Debug issues across data pipelines, integrations, model outputs, and the broader technical stack.
- Prototype solutions, identify productization opportunities, and document architectures, integration patterns, and best practices.
Requirements
- 8+ years of software engineering experience with strong data structures, algorithms, and system design fundamentals.
- Production Python expertise and experience with modern AI/ML frameworks such as LangChain, LlamaIndex, HuggingFace, or the OpenAI API.
- Experience with cloud platforms such as AWS, GCP, or Azure and modern data infrastructure.
- Strong problem-solving skills for navigating ambiguous requirements and rapidly iterating toward solutions.
- Excellent communication skills for explaining complex technical concepts to technical and non-technical audiences.
- Deep understanding of LLMs, prompting techniques, embeddings, and RAG architectures is preferred.
- Production experience building and deploying AI agents or autonomous systems is preferred.
- Knowledge of vector databases and semantic search systems is preferred.
- Experience with Docker, Kubernetes, CI/CD pipelines, Terraform, Bicep, or other infrastructure-as-code tools is preferred.
- Experience in DevOps, platform, or infrastructure roles and familiarity with SOC 2, GDPR, HIPAA, security, compliance, or governance requirements is preferred.
- Technical consulting, solutions engineering, product engineering, technical enablement, or teaching experience is preferred.
Benefits
- Comprehensive health, dental, and vision coverage.
- Retirement benefits.
- Learning and development stipend.
- Generous paid time off.
- Potential commuter stipend.
- Full-time role; location-specific position in San Francisco, New York, or Seattle.
- 90-day waiting period before reconsideration for the same role.
Categories
About Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. We 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. The Scale Generative AI Platform allows customers to build, evaluate, and control advanced AI agents and applications that continuously improve. The Scale Data Engine provides the technology to collect, curate, and annotate high-quality datasets. Through our Scale Labs, we test models with rigorous benchmarks and novel research to ensure breakthroughs translate into systems people can trust. Scale powers the most advanced LLMs and generative models in the world through RLHF, data generation and model evaluation. We work 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.