Senior Data / AI Application Engineer

Overview

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC 

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA 

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence. 

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management. 

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage. 

Job Description

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 Own

• Internal 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

Your Experience Includes

• 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

Nice to Have

• 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

Salary Range for this role: $185,000 - $200,000

DDN

DDN has a very strong orientation towards these 4 characteristics and any successful employee will demonstrate these capabilities: 

Self-Starter - Takes independent action to identify and solve problems. Seeks out relevant information needed to make decisions. Gets involved with new initiatives. 

Success/Achievement Orientation - Delivers quality results consistently. Targets, achieves (or exceeds) measurable results. Sets challenging goals, focuses on critical priorities, and is accountable. 

Problem Solving - Recognizes problems and responds with a systematic assessment that identifies and addresses cause of issue. Practical, realistic, and resourceful. 

Innovative - Builds and improves key business processes that enhance the effectiveness of DDN. Generates new ideas, challenges the status quo, and solves problems creatively.

DataDirect Networks, Inc. is an Equal Opportunity/Affirmative Action employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

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