Role Description & Responsibilities
Data Engineering
About Scale AI
Scale AI is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Data Engineering role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems.
Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale.
Key Responsibilities & Day-to-Day Scope
- ✓ Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use.
- ✓ Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows.
- ✓ Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data.
- ✓ Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight.
- ✓ Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures.
- ✓ Own the full experimentation lifecycle, from hypothesis generation to production rollout.
- ✓ Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation.
- ✓ Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures.
- ✓ Continuously evaluate newly released frontier models and determine where they meaningfully improve quality, latency, reliability, or cost.
- ✓ Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback.
- ✓ Measure success through business outcomes, not benchmark scores.
Official Qualifications & Technical Requirements
- • Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost.
- • Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines that enable safe deployment in high-stakes environments.
- • Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments.
- • Build human-in-the-loop workflows that effectively combine AI automation with expert oversight.
- • Partner directly with enterprise customers to understand their business, data, and operational challenges.
- • Translate ambiguous customer problems into production AI architectures.
- • Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems.
- • Identify reusable patterns that become core capabilities across many enterprise deployments.
- • Designing reasoning and agent architectures
- • Building retrieval, memory, and customer intelligence systems
Preferred Skills & Technology Stack
- + Experience with big data tools (Apache Spark, Kafka, Flink) and cloud platforms (AWS, Azure, GCP).
- + Familiarity with dbt (data build tool) for SQL transformations.
- + Hands-on experience with Docker and Linux system administration.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Scale AI
Verified EmployerScale AI champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.