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Lead Software Engineer - Content Systems
ParamountNew York City, United Statesfull_timeVerifiedPosted 9 Jun 2026
💰 $235,200/yr($156,800/yr – $235,200/yr)
About the role
#WeAreParamount 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.
Lead Software Engineer, CMS Platform
We are looking for a Lead Software Engineer to drive the technical direction of our Content Management System platform at Paramount Streaming. This is a hands-on individual contributor leadership role — you will write production code, own architectural decisions, and raise the technical bar across a polyglot platform that powers content delivery for Paramount+, Pluto TV, and CBS.com across multiple regions.
You will lead a team of 2–5 engineers through influence, not authority. No direct reports — maximum technical impact.
Responsibilities
Technical Leadership & Architecture
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Serve as the established technical owner of one or more core CMS systems (API layer, integration services, search pipeline, or admin UI).
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Drive architectural decisions across the CMS platform, including API design, data modeling, event-driven integrations, and search infrastructure.
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Lead the design and implementation of scalable, robust services across a polyglot stack: Java/Spring Boot APIs, Next.js/React frontends, Python services, Kafka/PubSub messaging, and Solr search pipelines.
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Define and promote engineering best practices. This includes coding standards, design patterns, testing strategies, documentation, and AI-augmented workflows. Explain what team members do well and where they need supervision. Describe how we maintain code quality while increasing output.
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Identify, prioritize, and strategically reduce technical debt across the domain.
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Write and review RFCs, architecture decision records, and technical design documents for significant changes.
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Set the team's bar for AI-assisted development — including review standards for agent-generated PRs, prompt and context patterns (e.g., CLAUDE.md / agent instructions), and how we measure quality at higher delivery speed.
Delivery & Execution
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Stay involved in coding. Write important production code. Run explorations to reduce risks in architecture decisions. Build prototypes. Help with high-impact features.
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Lead large projects and initiatives from conception through delivery — break down ambiguous, large-scale problems into actionable work.
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Coordinate rollouts and releases across multiple teams and services effectively.
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Partner with product managers, stakeholders, and other scrum teams to shape technical roadmaps that connect engineering work to business outcomes.
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Assess technical risk, make pragmatic trade-off decisions, and communicate them clearly.
Operational Excellence
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Own end-to-end delivery: from design through production observability and reliability.
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Fulfill SLAs by participating in on-call rotation, leading incident resolution, conducting RCAs, and driving preventive improvements.
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Set a high bar for quality through automated testing, peer review, CI/CD pipelines, and observability (structured logging, metrics, alerting).
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Ensure platform reliability across multi-region deployments (US, International, Pluto TV).
Mentorship & Culture
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Mentor and coach engineers through code reviews, design sessions, pairing, and architectural guidance — other engineers seek you out for this.
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Raise the technical bar for the entire team systematically, not just through individual contributions.
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Influence engineering culture: advocate for higher product quality, engineering efficiency, and continuous improvement.
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Help expand the team through interviewing candidates and onboarding new team members.
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Facilitate knowledge sharing across the team — tech talks, documentation, cross-training on system areas.
Cross-Functional Collaboration
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