We’re looking for a Senior Software Engineer to build internal applications on top of DDN’s enterprise data platform. This is a largely greenfield charter — a new function dedicated to full-stack tools and AI-powered services for GTM, Finance, Support, and Product. We are building applications that surface data for decision-making and applications that improve and automate the operational processes that run the business. You’ll have early prototypes to learn from, but the mandate is to define this product portfolio and build it out. Data and analytics engineers own what’s underneath; the applications themselves — frontend, backend, deployment, model integration — are yours.
What You’ll OwnInternal applications — design, build, and operate full-stack web apps (FastAPI/Flask + React/TypeScript today, but technology choices are open) that put data and AI into stakeholders’ hands — both as decision-support interfaces and as purpose-built tools that let them do operational work
AI/LLM integration — build features powered by LLMs and ML — classification, extraction, summarization, copilots, agentic workflows — choosing whichever models, providers, and frameworks fit the problem
Application infrastructure — deploy and operate apps on GCP (App Engine, Cloud Run, GKE), connect them to the data platform, manage auth, own CI/CD and app security
Product surface — define what good looks like for this new function: which problems are worth a custom app vs. a BI dashboard, what our reusable building blocks should be, and how we ship reliable, observable services people depend on
Collaboration — partner with stakeholders to scope the right tool for the job, with analytics engineers to shape the underlying data models, and with data engineers on platform constraints
5+ years building production software, with meaningful time spent on full-stack web applications
Strong Python — APIs (FastAPI, Flask, or similar), data access patterns, packaging, testing
TypeScript/React (or comparable framework), component design, interactive data UIs
Hands-on experience with GCP application services — App Engine, Cloud Run, GKE, IAM
Strong SQL and comfort working with cloud data warehouses (BigQuery in our case) — you can write a query, understand its cost, and design an app’s data access layer around it
Experience developing and deploying AI/LLM-powered applications in production — prompt design, structured output, evaluation, cost/latency tradeoffs, awareness that the model and tooling landscape changes quickly
Experience operating what you ship — logging, monitoring, error handling, debugging in production
Experience with software engineering best practices: CI/CD, automated testing, observability, secure application design
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
Experience building AI-native applications such as text-to-SQL interfaces, copilots, agentic workflows, or automated insight-generation systems
Hands-on experience with one or more LLM provider APIs (Anthropic’s Claude, OpenAI, Google, open-weight models, etc.) and agent frameworks (Claude Agent SDK, LangGraph, or similar)
Experience with managed AI/ML platforms (Vertex AI, SageMaker, or similar) — model serving, embeddings, evaluation tooling
Familiarity with dbt and modern data warehouse patterns from a consumer’s perspective
Experience with Airflow for triggered jobs and background work
Familiarity with Terraform for managing application infrastructure
Background designing data-heavy UIs — tables, drill-downs, large result sets, interactive exploration
Prior experience as the first or only application engineer on a data team — comfort owning the full lifecycle
Skills Required
- 5+ years building production software, including substantial full-stack web application experience
- Strong Python experience with APIs, FastAPI, Flask, data access patterns, packaging, and testing
- TypeScript and React, or a comparable frontend framework, with component design and interactive data UI experience
- Hands-on experience with GCP application services, including App Engine, Cloud Run, GKE, and IAM
- Strong SQL skills and experience with cloud data warehouses, preferably BigQuery
- Production experience developing and deploying AI or LLM-powered applications
- Experience with prompt design, structured output, evaluation, and AI cost and latency tradeoffs
- Experience operating production software, including logging, monitoring, error handling, and debugging
- Experience with CI/CD, automated testing, observability, and secure application design
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- Experience building AI-native applications such as text-to-SQL interfaces, copilots, agentic workflows, or automated insight-generation systems
- Experience with LLM provider APIs and agent frameworks
- Experience with managed AI/ML platforms such as Vertex AI or SageMaker
- Familiarity with dbt and modern data warehouse patterns
- Experience with Airflow for triggered jobs and background work
- Familiarity with Terraform for application infrastructure
- Experience designing data-heavy user interfaces
- Experience as the first or only application engineer on a data team
What We Do
DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.
