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AtScale is the semantic layer for modern data and AI, connecting cloud data platforms like Snowflake, Databricks, and Google BigQuery with business users, BI tools, and AI agents. The company enables consistent, governed, AI-ready analytics, with the semantic layer serving as the foundation for trustworthy AI answers in production.
You will lead the AI team responsible for building AtScale's GenAI capabilities. This is a player-coach role where you set technical direction for how large language models and agents integrate with the semantic layer, plan and deliver the roadmap with your team, and write production code weekly. You'll collaborate closely with product management, core engine and platform teams, and DevOps to turn AI ideas into customer-facing features.
Key responsibilities include:
- Lead, hire, mentor, and grow a team of AI engineers with clear expectations, timely feedback, and a culture emphasizing quality, ownership, and curiosity
- Define architecture and standards for GenAI work, including agent and tool-calling patterns and evaluation frameworks
- Translate product goals into actionable plans, milestones, and sprint-level work; scope projects realistically and manage risk and dependencies
- Design and productionize GenAI solutions using foundation model APIs and frameworks; lead by example in design and code reviews
- Establish evaluation standards for AI output across accuracy, bias, latency, cost, and compliance; build measurement and observability systems
- Partner with DevOps, product, and engineering teams to integrate models into the platform, debug AI-generated responses, and maintain production stability
- Communicate technical direction and results to engineering leadership, product, and customers; engage in technical customer conversations
Requirements:
- 2+ years as a tech lead or engineering manager of an AI or ML team, with continued hands-on coding
- 10+ years of software engineering experience, including 7+ years developing AI algorithms or technologies
- Shipped GenAI features to production at scale
- Fluent in Python and the modern GenAI stack: foundation model APIs, retrieval-augmented generation, embeddings, prompt and context engineering, systematic evaluation
- Comfortable with Docker/Kubernetes, Git/CI/CD, and debugging customer systems
- Strong ability to translate ambiguous goals into executable plans; clear communication with engineers, product managers, and executives
- Preference for quality over speed; current with AI tooling; thrives in fast-paced environments with shifting priorities
- Based in or able to work Eastern Time hours, overlapping with 10 AM–5 PM ET core collaboration window (EST/CST preferred)
Preferred qualifications:
- Experience with semantic layers, BI, OLAP, or analytical SQL
- Understanding of how analysts and business users query data
- Hands-on work with natural-language-to-query systems, agent frameworks, or Model Context Protocol (MCP)
- Familiarity with Scala or JVM ecosystem (AtScale's core engine)
- Experience building LLM evaluation harnesses, red-teaming, or AI governance programs for enterprise customers
- Contributions to open-source AI tooling or published talks/writing on applied GenAI
