Sr. Data & AI Application Engineer

Job Requirements

About the Role
We're looking for a senior, technically curious full-stack engineer to lead development of the platform our team is building - a unified UI for Insights, Audience Building, and Measurement powered by large-scale data and AI. This is a hands-on senior/lead role. You'll set technical direction, own architecture decisions, and work alongside other engineers on real production systems - not toy projects - spanning Snowflake data clean rooms, AI-powered chatbots, lookalike audience modeling, measurement analytics, data insights, and emerging R&D initiatives.

You'll be the kind of engineer who has shipped enterprise-grade applications before and knows how to integrate cleanly with embedded third-party SaaS services without creating a fragile mess. This role is ideal for someone who asks, "why does this work?" not just "does it work?" - and who's energized by owning a platform end to end.

Responsibilities
Lead the design and front-end development of our platform UI (Insights, Audience Building, Measurement) using React and Node.js (Next.js preferred)
Architect enterprise-grade systems with clean dependencies on embedded/third-party SaaS services (e.g.

Snowflake, Thoughtspot)
Design and build data pipelines, clean room configurations, and semantic layer definitions on Snowflake
Develop and maintain AI-powered chatbots, MCP integrations, and Slack/API-connected tools
Support audience modeling workflows including model training, scoring, calibration, and attribute enrichment and audience distribution
Build measurement frameworks, dashboards, and reporting pipelines (e.g., ThoughtSpot embedded) to surface insights from large-scale datasets
Fulfill custom data and analytics requests - segmentation, overlap analysis, behavioral profiling, and adhoc pulls
Prototype and document R&D initiatives around privacy-preserving computation and AI agent orchestration
Set engineering conventions, mentor teammates, and help guide technical decisions for the platform
Build clean, documented code and manage work through Git/Bitbucket with JIRA-based branching conventions
Required Qualifications
BS or MS in Computer Science, Data Science, or Information Systems, with 6-8 years of related experience
Proven experience architecting and shipping an enterprise-level application with a polished UI and dependencies on embedded/third-party SaaS services
3-6 years building big-data-driven web applications with Node.js, Next.js, and React
Strong proficiency in SQL - comfortable writing complex queries, window functions, CTEs, and aggregations
3-6 years of Python programming - data manipulation, scripting, API calls, and basic OOP
Exposure to at least one cloud data platform (Snowflake, BigQuery, or Redshift)
At least 3 years of REST API and data pipeline experience
Familiarity with SSO, authentication, and identity concepts (e.g., AWS Cognito)
Ability to work independently, manage your own time, and communicate clearly in a fully remote environment

Preferred Qualifications
Experience building with GenAI coding and agentic developer tools (e.g., Amazon Kiro, Claude Code, Cursor, Copilot, or agent orchestration frameworks) - a big plus
Hands-on experience with Snowflake Cortex, Snowpark, or Streamlit
Familiarity with LLM APIs (Anthropic Claude, OpenAI) and prompt engineering patterns
Exposure to ML classification models, feature engineering, Platt calibration, or model evaluation techniques
Knowledge of data privacy concepts - data clean rooms, differential privacy, or privacy-enhancing technologies (PETs)
Experience with Slack Bolt, AWS EC2, or deploying Python applications to cloud infrastructure
Familiarity with MCP servers or AI agent orchestration frameworks
Experience working with large-scale behavioral or transaction datasets (100M+ rows)
Background in Adtech/Martech, marketing analytics, audience segmentation, or measurement - not required, but a strong bonus, since it's the vertical our platform serves
Tech Stack You'll Touch
Snowflake, Snowpark Python, Snowflake Cortex, Streamlit, Python, SQL, ThoughtSpot BI, Next.js, React, Node.js, AWS Cognito, Claude API, Model Context Protocol (MCP), Slack Bolt, AWS EC2, Bitbucket, JIRA, plus modern GenAI coding tools.