What You'll Be Part Of:

At iSpot.tv, we deal with BIG data, operating in a high-scale AWS environment with thousands of servers processing massive streams of media metadata. Our Publisher Team within the Creative, Audience, and Outcomes (CAO) pillar is where AI meets measurement at scale: rethinking how publishers understand their audiences, how outcomes are attributed, and how data pipelines power our industry-leading measurement platform.

As an SDE 2 on this team, you've moved past foundational learning and are a competent, independent contributor who owns meaningful parts of our system. You'll ship production services end-to-end, make architectural calls within your scope, and help raise the bar for how the team builds with AI as a first-class development partner. This is a strong fit for engineers who want real ownership, work alongside AI specialists and senior engineers solving novel problems, and operate in an environment where AI is a genuine teammate in the development loop.

Your Impact

1. Technical Excellence & Domain Ownership

• Feature Ownership: You own features end-to-end—design, build, ship, and iterate on AI-driven capabilities across data pipelines, APIs, and agent workflows, from technical design through production rollout.

• Coding & Debugging: You are competent in programming and debugging across multiple components and environments. You write high-quality code that includes monitoring, metrics, and logging as standard practice.

• Scoped Technical Decisions: You choose the right tradeoffs on services and components you own. You bring proposals and prototypes to design discussions rather than waiting for direction.

• Testing & Quality: You author and own the testing plan for your features, considering product requirements and edge cases. You perform unit, component, integration, and E2E testing and can differentiate between application bugs and environment issues.

• Code Reviews: You actively participate in code reviews, following team guidelines and best practices to ensure the collective codebase remains healthy, maintainable, and sets the standard for the next engineer who touches it.

2. AI-Driven Productivity & Efficiency

• AI-First Workflow: You independently use AI tools (e.g., Kiro, Copilot, Gemini, Cursor) to improve the speed and quality of your work. This includes using AI for code understanding, self-code reviews, and ramping up quickly in new domains or languages.

• Critical Evaluation: You don't blindly accept AI-generated output. You critically evaluate it for correctness, security, and alignment with iSpot standards before relying on it.

• Team Uplift: You help the team get better at working with AI—share patterns that work, flag the ones that don't, and identify enhancements that automate repetitive tasks so you can focus on solving complex problems.

3. Operational Excellence & Data Strategy

• Production Reliability: You monitor performance, scalability, and cost of the services you build. You respond when things break and participate in the on-call rotation.

• Incident Management: You promptly investigate test failures and production alerts. You are developing the ability to perform Root Cause Analysis (RCA) with limited guidance and contribute to improving system resilience.

• Rapid Iteration: You move fast on prototypes—taking MVPs from idea to validated learning quickly—and know when to harden versus when to throw away.

• Continuous Improvement: You engage with DORA metrics, AI adoption, and PR cycle time as a lean operating model, not as reporting overhead.

• Modern DevOps: You contribute to CI/CD pipelines with human-in-the-loop checks where they matter, driving quality through the full software lifecycle.

4. Collaboration & Growth

• Independence: You complete most assignments independently with little to no supervision, knowing exactly when and how to escalate issues to your manager or senior leads.

• Team Contribution: You help onboard and train new team members and are proactive in building trust through excellent follow-through and integrity.

• Communication: You communicate clearly and concisely, sharing opportunities to improve deliverables or work processes. You work cleanly across engineering, product, and data science.

What You Bring

• Experience: 3–5 years of professional software engineering experience building and operating production systems.

• Technical Proficiency: Strong programming depth in at least one of Java, Python, TypeScript, or Go—and comfort picking up another quickly.

• Demonstrated Ownership: A track record of owning non-trivial features or services in a production environment, including the operational side.

• Cloud Foundation: Solid understanding of AWS (S3, Lambda, EC2) and containerization (Docker).

• Tech Required: Java, MySQL, Git, CI/CD pipelines, REST API design.

• AI Native: Demonstrated ability to use LLMs and AI coding assistants to accelerate your development lifecycle.

• Soft Skills: Strong communication skills with the ability to tailor messaging to different audiences. Excellent problem-solving and analytical skills with a bias for action.

• Education: Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

Preferred Skills

• Knowledge of Infrastructure as Code (Terraform) and CI/CD tooling (CircleCI).

• Experience in Ad-Tech or high-throughput "Big Data" processing environments.

• A genuine interest in automation, experimentation, and where AI tooling is headed.