Head of Engineering, Applied AI

Job not on LinkedIn

🔥 13 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

👮‍♀️ Software Engineering Manager

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Theta

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

💼 Consulting

📣 Marketing

💸 Finance

Consulting • Marketing • Finance

Theta is a company specializing in predictive customer analytics and corporate valuation. It offers innovative solutions to understand and forecast customer behavior through its advanced Customer Lifetime Value (CLV) model, CLV Ultra. Designed for both investment firms and corporations, Theta helps clients enhance their marketing strategies, improve customer engagement, and make informed business decisions by providing deep insights into customer unit economics and corporate valuation methodologies.

📋 Description

• Own Theta’s engineering and lead the data science team, with most time spent building • Set technical direction and help the team resolve difficult delivery problems • Work with clients’ technical teams • Architect reliable execution of thousands of models on cloud infrastructure • Work with client engineering teams to package and deploy models in their own environments • Make the pipeline from raw client files to validated model outputs reliable and reusable • Develop AI-assisted workflows for data preparation and modeling • Set standards for testing, validation, and reliable deployment • Review the team’s code and designs • Decide what to build, automate, or outsource while ensuring maintainability • Help data scientists resolve difficult client delivery problems and contribute directly when engagements overlap

🎯 Requirements

• Deep engineering skills and curiosity and judgment to work across engineering, data science, and client delivery • Built and operated production data or ML systems end to end at scale on cloud infrastructure • Cloud infrastructure experience; GCP preferred, with AWS, Azure, Databricks, or Snowflake also relevant • Experience solving problems across data preparation, model execution, and infrastructure, from messy input files to slow model runs • Critical evaluation of data and outputs, including knowing which issues should stop a run • Willingness to learn and work in the existing R-based production stack • Product engineering mindset balancing reliability, usability, and delivery needs • Ability to lead a small, experienced data science team through hands-on technical guidance and difficult delivery problems • Comfortable participating in client calls to explain technical methods and trade-offs, discuss data requirements, and understand clients’ technology stacks and infrastructure • Genuine interest in developing AI-assisted workflows, learning unfamiliar tools quickly, and critically evaluating their outputs • Preferred: Experience building and evaluating AI-assisted workflows for data preparation and modeling, including LLM or agent-based systems • Preferred: Production R experience, including packaging, dependency management, containers, or C++ integration through Rcpp • Preferred: Statistical modeling, especially familiarity with CLV or BTYD models • Preferred: Experience deploying data or modeling workflows in client-controlled environments, including Databricks, Snowflake, or Spark • Preferred: Infrastructure as code experience, such as Terraform or similar, and CI/CD