Software Development Engineer 1

iSpot.tv, Inc.•Bellevue, WA

43d•Hybrid

About The Position

You will be part of iSpot's AI Team, focused on bringing AI-powered innovation to life across our Creative, Audience, and Outcomes (CAO) pillars. The team's mission is to deeply integrate AI into every aspect of our measurement platform. This is a rare opportunity to work at the intersection of data, AI, and engineering excellence-helping shape how the next generation of iSpot products are imagined, built, and deployed.

Requirements

Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
0-2 years of experience in software engineering with strong programming skills in Java, Python, TypeScript, and/or Go.
Familiarity with modern development practices: Git, CI/CD pipelines, REST APIs, cloud environments (AWS preferred).
Understanding of basic ML/AI concepts or willingness to learn rapidly.
Excellent problem-solving skills with a bias for action and learning.
Strong communication skills and the ability to collaborate in cross-functional teams.

Nice To Haves

Exposure to LLM or generative AI tools (e.g., OpenAI API, LangChain, or similar).
Experience with data processing frameworks (Spark, Airflow) or vector databases.
Knowledge of containerization and orchestration (Docker, Kubernetes).
Familiarity with frontend development (React, Next.js) is a plus.
Passion for automation, experimentation, and working in a fast-paced, evolving AI ecosystem.

Responsibilities

Collaborate with senior engineers and AI specialists to design, build, and deploy AI-driven product features and tools.
Develop, test, and maintain high-quality, production-grade code for data pipelines, APIs, and autonomous agent workflows.
Work within an AI-first development environment, using AI copilots for coding, testing, and documentation.
Participate in sprint planning, code reviews, and retrospectives to ensure high standards of quality and collaboration.
Implement continuous integration and delivery (CI/CD) pipelines with human-in-the-loop validation.
Contribute to prototype and MVP development cycles, iterating quickly on ideas to validate impact.
Monitor performance, reliability, and scalability of AI-driven systems and services.
Learn and apply the team's operating model-lean, agile, and metrics-driven (DORA, AI adoption, PR cycle time).

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