Staff+ Software Engineer, Caching

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. About the team The AI/ML Platform pod builds Fanatics' internal AI platform: the paved road for every team building with LLMs, MCPs, and agents. Gateway, agent runtime, registry, retrieval, evaluation, and cost analytics, all running on a petabyte-scale lakehouse with enterprise-grade governance. You'll join a pod that owns this platform end to end. This is a Staff-level role, and a hands-on one. You will choose the architecture, define the standards other teams build to, and stay in the code, shipping the hardest parts yourself. The decisions you make are ones the organization lives with for years. Responsibilities • Own the end-to-end architecture of the AI control plane: gateway, agent runtime, registry, retrieval, evaluation, and cost. Set technical direction, sequence the roadmap, and make the build-versus-buy calls. • Build the enterprise LLM gateway: multi-provider routing, failover, caching, rate limiting, token optimization, and key management, with a path to self-hosted open-weight models where cost, latency, or data residency call for it. • Build the Agent/MCP ecosystem on a managed runtime such as AWS BedrockAgentCore: enterprise systems exposed as governed tools over MCP, a control-plane registry for discovery,

P-1416 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, Databricks has started a multi-year journey to build the best Data Intelligence Platform. For this we are building on top of a great foundation but our goal is to go further to build dramatically better products. From the Storage Engine (data layout, encryption, caching, ...) to the Query Engine (Vectorization, Query Optimization, …), we want to revisit every component to provide our customers with the fastest, easiest to use and most secure data platform for all their data workloads. As a software engineer, you will join as a founding member of the not only the Belgrade site, but really as a founding team for our multi-year journey to achieve our Lakehouse vision. You will be involved in the entire development cycle and exemplify all core Databricks values (own-it, data decide, teamwork, customer-obsessed). The responsibilities you will have : Drive requirements clarity and design decisions for ambiguous problems Produce technical design documents and project plans Develop new features Mentor more junior engineers Test and rollout to production, monitoring. What we look for: BS in Computer Science or equivalent practical experience in databases or distributed systems Comfortable working towards a multi-year vision with incremental deliverables Motivated by delivering customer value and impact 8+ years of production level experience in either Java, Scala or C++ Solid foundation in algorithms and data structures and their real-world use cases Experience with distributed systems, databases, and big data systems (Apache Spark™, Hadoop) About Databricks Databricks is the Data and A

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role We are currently seeking a Staff Software Engineer to join the Calculation Engines team which operates the critical servers, caching layers, and communication protocols which power Addepar’s financial analytics and reporting product. More than 95% of all Addepar traffic flows through this infrastructure; you will be responsible for the next generation of development, tooling, and CI/CD systems which empower Addepar to serve our clients. Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment. What You’ll Do Design and build distributed microservice components in Addepar’s calculation engine - a data intensive application Scale our Java-based calculation engine to 100x larger workloads using best-of-breed time series analytics database technologies Get involved in the decision process to make the best decision to scale with the consideration of data consistency, throughput, speed, operability and cost Profile and improve system efficiency in a highly concurrent platform Who You Are 7+ years of software en

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry's largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. As a Staff Software Engineer on our Inference team , you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary. Strong candidates may also have experience with: High-performance, large-scale distributed systems Implementing and deploying machine learning systems at scale Load balancing, request routing, or traffic management systems LLM inference optimization, batching, and caching strategies Kubernetes and cloud infrastructure (AWS, GCP) Pytho

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

About the Team The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Key Value team owns the storage platform that powers business-critical workloads across DoorDash, Wolt, and Deliveroo. These systems sit on the Tier-0 critical path. They serve millions of QPS across multiple regions and underpin how hundreds of engineering teams build reliable systems at massive scale. About the role DoorDash's storage abstraction platform is a unified data-access layer that sits in front of our databases and decouples application teams from the underlying storage engines, similar to modern data-gateway and key-value / time-series data-abstraction platforms. Nearly every request that touches persistent data flows through it. As DoorDash scales 10x–100x across new verticals, global expansion, and acquisitions, this platform is where the hardest distributed-storage problems live — latency at the tail, request routing, and reliability under exponential load. We're hiring a Staff Software Engineer to be the domain specialist for the storage abstraction platform: a deep, opinionated technical leader who owns the reliability, performance, and correctness of the platform at scale, sets its technical direction, and raises the execution bar across the storage organization. You must be located in the New York Metro Area, Bay Area or Seattle for this hybrid position. You will report to the Engineering Manager on our Distributed Key Value team within the Storage organization. You're excited about this opportunity because you will… Own the reliability, performance, and correctness of the storage abstraction platform at scale, independently leading resolution of mission-critical issues in ambiguous, high-pressure situations. Set technical direction for the platform — the storage abstraction and data-access layer, provider model, caching, and rou