Software Development Engineer 1

iSpot•Bellevue, WA

1d•Hybrid

About The Position

As a member of iSpot’s Publisher Team , you will be at the forefront of bringing AI-powered innovation to our Creative, Audience, and Outcomes (CAO) pillars. Our mission is to move beyond simple automation and deeply integrate artificial intelligence into every layer of our industry-leading measurement platform. This is a rare opportunity to work at the intersection of big data, AI, and engineering excellence. You will help shape how the next generation of iSpot products are imagined, built, and deployed in an environment where AI is a core teammate, not just a tool.

Requirements

Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Experience: 0–2 years of professional software engineering experience.
Technical Proficiency: Strong programming foundations in Java, Python, TypeScript, and/or Go .
Modern Tooling: Familiarity with Git, CI/CD pipelines, REST APIs, and cloud infrastructure ( AWS preferred ).
AI Foundations: A solid understanding of basic ML/AI concepts or a demonstrated ability to learn complex new technologies rapidly.
Soft Skills: Excellent problem-solving abilities with a "bias for action" and strong cross-functional communication skills.

Nice To Haves

Hands-on exposure to LLMs or generative AI frameworks (e.g., OpenAI API, LangChain , etc.).
Knowledge of containerization and orchestration ( Docker, Kubernetes ).
Familiarity with modern frontend development ( React, Next.js ).
A passion for automation, experimentation, and evolving AI ecosystems.

Responsibilities

Collaborative Development: Partner with senior engineers and AI specialists to design, build, and deploy AI-driven product features.
Full-Stack Engineering: Develop, test, and maintain production-grade code for data pipelines, robust APIs, and autonomous agent workflows.
AI-First Workflow: Operate within an AI-native development environment, leveraging AI copilots for coding, testing, and documentation to maximize efficiency.
Agile Delivery: Participate in sprint planning, code reviews, and retrospectives to ensure high standards of quality and teamwork.
Modern DevOps: Implement and manage CI/CD pipelines incorporating human-in-the-loop validation for reliable deployments.
Rapid Iteration: Contribute to prototype and MVP cycles, moving quickly from ideation to validation to measure real-world impact.
System Health: Proactively monitor the performance, reliability, and scalability of AI-driven services.
Metrics-Driven Growth: Adopt the team’s lean operating model, focusing on DORA metrics, AI adoption rates, and optimized PR cycle times.