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Principal Software Engineer

Job in Burbank, Los Angeles County, California, 91520, USA
Listing for: Paramount
Full Time position
Listed on 2026-05-06
Job specializations:
  • Software Development
    Software Engineer, AI Engineer, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

#We Are Paramount  on a mission to unleash the power of content... you in?

We've got the brands, we've got the stars, we've got the power to achieve our mission to entertain the planet - now all we're missing is... YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter - both for our audiences and our employees - and aim to leave a positive mark on culture.

Job Title :
Principal Software Engineer - AI Tooling & Quality Engineering Platforms

Team :
Global Quality Engineering (GQE)

Location :
New York City, Los Angeles, San Francisco

Overview

Paramount Skydance Corp. is seeking a Principal Software Engineer to architect, build, and scale AI‑driven tooling and engineering platforms that accelerate quality, automation, and developer productivity across the Global Quality Engineering organization. This is a senior technical leadership role focused on designing intelligent systems, internal developer tools, and automation accelerators that elevate testing maturity and modernize how GQE delivers quality  will partner closely with engineering, platform, and data teams to build AI‑powered solutions that streamline test creation, triage, analysis, and execution.

This role requires deep software engineering expertise, deep architectural judgment, and hands‑on experience applying LLMs, retrieval systems, and automation frameworks to real engineering workflows. This is not a traditional "in test" role. You will be building AI platforms, internal tools, and automation accelerators that enable hundreds of engineers across GQE.

Key Responsibilities

AI Tooling Architecture & Platform Development

  • Design and build AI‑powered tools that accelerate test creation, code generation, defect triage, log/telemetry summarization, and root‑cause analysis.
  • Architect retrieval‑augmented generation (RAG) systems, embeddings pipelines, and domain‑specific LLM integrations tailored to GQE workflows.
  • Develop internal developer tools, CLIs, services, and micro‑platforms that integrate seamlessly with existing automation frameworks and CI/CD systems.
  • Build scalable APIs and services that expose AI capabilities to GQE teams across brands and platforms.

Intelligent Automation & Quality Acceleration

  • Create systems that automatically evaluate test failures, classify flakiness, detect patterns, and recommend fixes.
  • Build AI‑assisted test authoring tools that generate high‑quality test scaffolds, assertions, mocks, and data models.
  • Integrate AI‑driven insights into CI/CD pipelines to reduce triage time, improve signal quality, and accelerate release readiness.
  • Partner with automation framework owners to embed AI capabilities into existing Java‑based frameworks.

Engineering Excellence & Technical Leadership

  • Serve as a senior technical leader leading the vision for AI‑enabled quality engineering across the organization.
  • Mentor engineers across GQE on AI tooling, platform engineering, and modern software development practices.
  • Evaluate emerging AI technologies, frameworks, and platforms to identify practical, high‑impact opportunities.
  • Establish engineering best practices for reliability, observability, performance, and maintainability of AI systems.

Cross‑Functional Collaboration

  • Partner with Platform Engineering, Data Engineering, Playback/Video Engineering, and Product teams to integrate AI tooling into core workflows.
  • Work with QE leadership to understand pain points, define requirements, and prioritize high‑value AI capabilities.
  • Collaborate with Dev Ops and CI/CD teams to ensure AI tools operate dependably in production pipelines.

Technical Execution

  • Build high‑performance backend services using Java, Kotlin, Python, or Node.js.
  • Implement vector databases, embeddings pipelines, and retrieval systems using tools such as Pinecone, Weaviate, FAISS, or Open Search.
  • Develop microservices, event‑driven systems, and distributed architectures deployed on Kubernetes and cloud platforms.
  • Integrate with Git Hub, Git Hub Actions, Jenkins, and internal automation frameworks to deliver seamless developer experiences.
Requ…
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