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Senior Principal Product Manager
Job in
San Francisco, San Francisco County, California, 94199, USA
Listed on 2026-03-02
Listing for:
Redis (redis.io)
Full Time
position Listed on 2026-03-02
Job specializations:
-
IT/Tech
AI Engineer
Job Description & How to Apply Below
Who we are
We're Redis. We built the product that runs the fast apps our world runs on. (If you checked the weather, used your credit card, or looked at your flight status online today, you’re welcome.) At Redis, you’ll work with the fastest, simplest technology in the business—whether you’re building it, telling its story, or selling it to our 10,000+ worldwide customers. We’re creating a faster world with simpler experiences.
You in?
- Define product vision/strategy; develop/communicate clear product vision/strategy for Redis’s AI offerings (semantic caching, vector memory, AI infrastructure capabilities), inference caching/routing;
- Align with Redis’ overall AI strategy; use Large Language Models (LLM)/Natural Language Processing (NLP) architecture [Transformer models (GPT-3.5/4/5, Codex, Gemini, Claude Sonnet, Mistral), Context window optimization (8k–32k)];
- Work on custom model development (Human Eval, MBPP benchmarks); preprocessing (tokenization, deduplication, syntax validation);
- Work with model deployment/GPU Infrastructure:
Azure ML deployment pipelines, model quantization (FP16, INT8); - Translate market trends, customer requirements, emerging technologies (LLMs, NLP) embeddings into detailed product requirements/development plans;
- Work with architects, engineers, internal/external stakeholders to define/write detailed product requirements;
- Analyze product telemetry/customer usage data to identify optimization opportunities; improve performance; inform data-driven product decisions;
- Evaluate trade-offs between model latency, accuracy, cost across different architectures;
- Design experiments/evaluation pipelines to guide technical decisions; develop proof-of-concept (POC) applications, demos, reference implementations (RAG workflows, LLM chatbots, AI agents) to demonstrate Redis’ AI capabilities;
- Partner with enterprise customers to understand AI workloads; design Redis-based architectures to meet scalability, latency, reliability requirements;
- Lead cross-functional product launches;
- Ensure alignment across engineering, marketing, sales, customer success for successful go-to-market executions;
- Evaluate third-party model deployment; serve solutions to provide recommendations to leverage external platforms versus in-house Redis AI capabilities, balancing performance, cost, control;
- Develop/maintain comprehensive technical documentation, best practices, architecture guides to enable customers/partners to implement/optimize Redis AI solutions; manage product’s lifecycle by maintaining backlog of features;
- Manage priorities;
- Ensure execution to specifications in accordance with Redis’ strategic goals; engage with customers/partners to understand needs;
- Gather feedback to inform product development;
- Define/analyze metrics that inform success of products;
- Track business impact using OKRs/KPIs; ensure compliant telemetry with engineering teams;
- Build/maintain relationships with key stakeholders, partners, potential customers;
- Generate buy-in/drive consensus across organizations;
- Drive decision making through user insights, quantitative analysis, AB testing;
- Stay updated with latest trends/ advancements in AI/ML technologies to integrate relevant innovations into product roadmap;
- collaborate with leadership, engineering, applied science, architecture teams to design foundational components to enable high-performance, low-latency AI applications.
- This is a telecommuting position with remote benefit from various unanticipated locations throughout the U.S.
- Master’s degree or foreign equivalent in Information Technology, Information Science, or Business Administration plus 2 years experience.
- Experience to include using LLM/NLP architecture [Transformer models (GPT-3.5/4/5, Codex, Gemini, Claude Sonnet, Mistral), Context window optimization (8k–32k)];
- Custom model development (Human Eval, MBPP benchmarks);
- Preprocessing (tokenization, deduplication, syntax validation)
- Working with model deployment/GPU Infrastructure:
Azure ML deployment pipelines, model quantization (FP16, INT8). - This is a telecommuting position with remote benefit from various unanticipated locations throughout the U.S.
Position Requirements
10+ Years
work experience
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