Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 7
API @ 7
CI/CD @ 3
Compliance @ 4
Data Engineering
Distributed Systems @ 4
GDPR @ 4
Go @ 7
Java @ 7
LLM @ 4
Marketing @ 4
Microservices @ 7
NoSQL @ 4
Observability @ 3
Python @ 7
SQL @ 4
Security @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking a Senior Platform Engineer to help build the platforms that power NVIDIA’s customer data, digital marketing, personalization, and AI-enabled marketing workflows. In this role, you will develop scalable backend services, data platform integrations, and reusable platform capabilities for customer activation, consent-aware experiences, campaign operations, and marketing intelligence.
Responsibilities
- Design, develop, and operate scalable backend services for customer profile, consent, personalization, campaign, and marketing platform capabilities.
- Build data-intensive services that integrate with document or NoSQL databases, relational databases, caching layers, search platforms, object storage, and messaging, pub-sub, or event-driven systems.
- Develop clean APIs, service-to-service integrations, authentication patterns, error handling, logging, caching, and reusable platform libraries.
- Contribute to customer data platform workflows, including audience activation, downstream system synchronization, campaign metadata, tracking, and data observability.
- Partner with marketing, product, analytics, data engineering, and AI platform teams to translate business needs into reliable technical solutions.
- Modernize existing platforms across database models, identity systems, profile services, consent workflows, and operational tooling.
- Apply AI-assisted engineering practices while maintaining strong ownership of architecture, testing, security, code quality, and production readiness.
- Improve reliability through observability, alerting, automation, anomaly detection, and practical incident prevention.
Requirements
- BS in Computer Science, Engineering, or a related technical field, or equivalent experience.
- 8+ years of software engineering experience building backend services, APIs, data platforms, and production systems.
- Strong experience with one or more modern programming languages like Java, Python or Go, along with microservices architecture, and API design.
- Hands-on experience with document or NoSQL database design, indexing, migration patterns, performance tuning, and operational best practices.
- Experience with relational databases, SQL, distributed systems, cloud infrastructure, and containerized production environments.
- Experience building systems that move customer, behavioral, consent, campaign, or audience data across platforms with strong attention to data quality, governance, and reliability.
- Familiarity with caching, search, messaging, pub-sub, object storage, CI/CD, observability, and production operations.
- Experience using AI-assisted engineering workflows responsibly while maintaining ownership of design, correctness, testing, security, and production readiness.
- Self-motivated and collaborative, with the ability to own complex projects, drive progress independently, and communicate technical tradeoffs clearly across distributed teams.
Ways to stand out from the crowd
- Working knowledge of GDPR, PIPL, and related data privacy compliance and regulatory practices.
- Experience building or operating customer data platforms, identity resolution systems, customer 360/profile services, consent platforms, audience activation workflows, personalization engines, or marketing activation systems.
- Experience modernizing backend or data services that handle customer, audience, consent, or campaign data, including data model evolution, database migrations, and production cutovers.
- Strong understanding of reliable customer data activation, including data quality, governance, consent enforcement, synchronization, recovery, and downstream reconciliation.
- Experience applying AI or LLM-based systems to audience intelligence, personalization, campaign operations, content workflows, data discovery, or platform automation.
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