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Qi Li shared this🚀 We're looking for a Principal Software Engineer, Data Platform at Salesforce. If you're passionate about architecting and building unified large-scale data platform infrastructure that powers millions of businesses worldwide — this is the opportunity for you. You'll be the technical north star for our Enterprise Data Platform, leveraging cutting-edge tech to power Business Intelligence, Advanced Analytics, and Generative AI. Location: #SanFrancisco, #Seattle or #NewYork Apply here: https://lnkd.in/g5Db-iXR
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Qi Li shared thisWe just announced Early Access for 3 powerful AI features: Flink Native Inference, Flink Search and Flink Built-in ML functions. Together, these capabilities simplify and accelerate real-time AI application development. See more details at https://lnkd.in/gvC2P7zP. Want to try these out? Sign up for Early Access (https://lnkd.in/gPVGqe6X). We’d love your feedback as we continue shaping the future of streaming AI Confluent processes 3+ Trillion messages per day and 1+ Exabyte of data per year, the AI journey just get started. Interested in building what's next? Joining Confluent ( https://lnkd.in/g7aFN7Es)New Confluent Cloud for Apache Flink® Capabilities Simplify Real-Time AI DevelopmentNew Confluent Cloud for Apache Flink® Capabilities Simplify Real-Time AI Development
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Qi Li shared thisI’m actively looking for experienced software engineers across the U.S. with a strong background in distributed database internals and a passion for building low-latency, scalable query processing systems on large datasets. I would love to hear from you if you’re excited about driving 0-1 innovation and working on high-impact, cutting-edge query processing initiatives! We have multiple openings at different levels (Senior, Staff, and Principal). Check out the Principal Engineer – Query Processing role that was just posted: https://lnkd.in/gd2RfhJf Join us and help shape the future of the Data Streaming Platform.
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Qi Li posted thisMy team is hiring Principal Software Engineers across the United States. Are you passionate about distributed database query processing and ready to take charge of architectural strategy and technical execution? This key strategic role will drive Confluent’s query processing initiatives, including cutting-edge areas such as query compilation and optimization, execution, vectorized runtimes, distributed shuffles, columnar storage, etc. If you have proven-track of leading large-scale OLAP style cloud databases and active contributions to relevant top open sources (Flink, Calcite, DataFusion, Celeborn, Clickhouse, Pinot, Arrow, Velox, Ray, etc.), I would love to hear from you! We are a remote-first company with a culture and tools to help self-motivated individuals thrive, no matter where or how you work. Please see the details and apply https://lnkd.in/gK2VVGy3
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Qi Li shared thisHighly recommend a fantastic resource for diving into machine learning! The machine learning specialization course from coursera.org is a top-notch program led by the renowned Andrew Ng. It's a great resource to brush up on fundamental theories and practical implementation. I suggest completing all optional Python, Tensorflow, and Keras coding exercises. Check it out here: https://lnkd.in/gxHm-ivv.Completion Certificate for Supervised Machine Learning: Regression and ClassificationCompletion Certificate for Supervised Machine Learning: Regression and Classification
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Qi Li shared thisVery happy for the strong partnership between Salesforce and Snowflake and the General Availability of Bring Your Own Lake (BYOL) Data Sharing with Snowflake from Salesforce. The Data Lake team at Snowflake is proud of our contribution with other sister teams and Salesforce . We are actively hiring. Please apply: Principal Software Engineer: https://lnkd.in/g8-ZxFw6 Senior Software Engineer: https://lnkd.in/gMQpwyZYSalesforce and Snowflake Make Data Sharing-Based Integration Generally Available, Helping Customers with Data-Driven EngagementSalesforce and Snowflake Make Data Sharing-Based Integration Generally Available, Helping Customers with Data-Driven Engagement
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Qi Li shared thisCome to join the #snowflake Data Lake team. We are in the beginning of a decade-long journey to build an easy-to-use, secure, performant, cost-efficient, feature-rich and open interoperable data lake product for enterprises of all size and scale. We just released the first Private Preview of our Unified Iceberg Table. Customer engagement is strong and expectation is high. I am actively hiring to accelerate the initiative. The location can be Bellevue, WA or San Mateo CA. I would love to speak with you if you have extensive experience in Database internal, Query engine, Big data internal, open source table format (Iceberg, Delta, Hudi) , Data Catalog and large distributed system. Please apply Principal Software Engineer https://lnkd.in/g8-ZxFw6 Senior Software Engineer https://lnkd.in/gMQpwyZY
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11mo
Congrats, Bo Chen !
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Qi Li liked thisQi Li liked thisDreamforce wrapped up yesterday with AIForce, Agent Fabric and many other AI announcements, and I’m proud of how our team brought that work to life for customers. Across presentations, campfire chats, and three days at the booths, the team shared how we’re are building AI agentic solutions, connect them to trusted data and tools, and put them to work inside Salesforce. A big thank you to everyone who presented and shared their experience: 🎤 “From API to Trusted Agent Tool with MuleSoft” Ashwani Tripathi Sudhanshu Joshi 🎤 “Automate Data 360 Pipelines via MuleSoft and Slack” Karthik Reddy Virginia Yee Derek Chan 🎤 “Orchestrate Multi-Agent Systems with Agent Fabric” Alfred Chen Eric Xu 🎤 “How Salesforce Uses Informatica and MuleSoft for Agentic AI” Sravan Kumar Vazrapu Shoban K Surya Kiran Chittiboyana 🎤 “How Salesforce Boosts Onboarding with Agentforce & MuleSoft” Venktesh Maudgalya Vikas Sangwan 🔥 “Customer Zero for MuleSoft (Campfire Chat)” Surya Kiran Chittiboyana Sravan Kumar Vazrapu Shoban K Amar Anuganti 🤖 At the Salesforce on Salesforce booth: “How Salesforce Boosts AI Analytics (MuleSoft Booth)” Thank you to the crew who kept the demos and customer conversations going throughout the conference: Alfred Chen Amar Anuganti Ashwani Tripathi Sudhanshu Joshi Karthik Kondagalla Shoban K Surya Kiran Chittiboyana Venktesh Maudgalya Vikas Sangwan These sessions showed the practical work that supports that direction: making APIs usable by agents, connecting trusted data, orchestrate multiple agents, and bringing AI into everyday workflows. There’s a lot of work behind every session and demo. Thank you to everyone who built, tested, and prepared this work, and to those who took on early booth shifts and made time for customer questions. To everyone who joined our sessions or stopped by the booth, thank you. Looking forward to continuing those conversations. #Dreamforce #Salesforce #MuleSoft #Agentforce #AgentFabric #Agents
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Qi Li liked thisGreat energy at the #Agentic Data Engineering session at #Dreamforce with Pratik Parekh , Joseph Pellissery and the team! 🚀 It was fantastic hearing the real-world data journey from Joseph and the Wescom Financial team, showcasing how organizations are building the right foundations for the agentic era. Massive shoutout to Makesh Renganathan as well for pulling off a stellar live demo under pressure in under 5 minutes. #DataEngineering #Salesforce #InformaticaQi Li liked thisThanks Joseph Pellissery from Wescom Financial and Vinay Gupta of Salesforce, our customer Zero to share their data journeys and vision at the #Agentic Data Engineering session today. Truly insightful conversations. And yes, Makesh Renganathan who did fantastic on my challenge to do a live and comprehensive demo in less than 5 mins. The recording should be available soon if you missed it. We are underway to prepare your data for agentic era. #Informatica #DataEngineering #Salesforce #Dreamforce
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Qi Li liked thisAt Dreamforce, we introduced Koa, Salesforce’s first CRM reasoning model, built on NVIDIA Nemotron. AI is getting smarter at an extraordinary pace. But the Agentic Enterprise needs more than intelligence. It needs AI that understands how businesses actually work, their context, workflows, policies, tools, and decisions. That’s why we built Koa. Koa brings nearly three decades of Salesforce CRM expertise into a purpose-built reasoning model for Agentforce. It is post-trained entirely on synthetic data across the customer lifecycle, runs inside the Salesforce trust boundary, and uses no customer data for training. And we’re already seeing what specialized intelligence can unlock: greater precision, reliability, and context retention across complex CRM tasks. Koa isn’t about one model replacing every other model. I believe the future is much more exciting than that. The future of enterprise AI is open, with the right model for the right job, surrounded by trusted context, actions, security, and control. Koa is an important step toward that future. A huge thank you to our teams at Salesforce and NVIDIA for bringing it to life. I can’t wait to see what our customers build with it. https://lnkd.in/gCFU6QcdQi Li liked thisMeet Koa, built on NVIDIA Nemotron Salesforce’s first CRM reasoning model for Agentforce just made its Dreamforce debut. → Built with 27 years of Salesforce CRM intelligence → Designed for complex, multi-step CRM work → Matches or exceeds leading model performance on CRM actions with 3x fewer errors 🚀 Now in pilot
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Qi Li liked thisQi Li liked thisIt's Dreamforce week! San Francisco is filling up with thousands of people looking for what's next in AI, and one of the biggest themes this year is Trusted Context: making sure AI agents act with the intelligence of your organization. Models on their own are brilliant. They're only brilliant for your organization when they're grounded in the truth of your business. So who builds that trusted context? It's a team sport, but data teams have an outsized role to play. All context starts as data. It has to follow the same governance rules we've long applied to humans, now extended to agents. It has to be refined from raw material into its distilled essence, shaped for an agent to use. The skills data teams have spent years applying to align companies on the right metrics now have to be applied to align agents on the right context. Over time, I expect the Chief Data Officer role to grow into a Chief Intelligence Officer role, accountable for grounding AI in the best truth of the business. At Salesforce, we've come to see that the value a data team provides IS the intelligence, and that intelligence is the product we deliver to the business. Every piece of intelligence, whether a metric, a fact, a memory, a model, a piece of knowledge, or an assembly of these, needs certification, lineage, quality indicators, and governance so the agent gets the distilled context it needs to do its job. When we talk about ontology, semantics, graphs, and the rest of the buzzwords, what we're really talking about is context: how do you take the shared understanding that lives in the neural networks of the humans who run your business and codify it so the neural networks of AI can understand it? Data teams have the chance to lead here, taking the skills they built in the digital revolution and using them to build the intelligence that fuels the agentic enterprise. Are you seeing your data teams step into this role? What will it take to build this trusted intelligence at scale?
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Qi Li liked thisQi Li liked thisMeet our judge: Jun Qian 🌟 Introducing Jun Qian, Vice President of Generative AI and Physical AI at Oracle, with over 25 years of experience building AI and machine learning technologies. Jun has led engineering teams at Oracle, Microsoft, and Amazon. At Oracle, he oversees the development of flagship AI solutions including Oracle Generative AI Service, Generative AI Agents, and Oracle Code Assist, bringing enterprise-grade AI to businesses and partners. We’re excited to have Jun join the Tech Impact Awards for AI 2026 jury! Three award tracks: 1. Builders: people building AI products and technology 2. AI Natives: professionals transforming their work with AI 3. Business: companies delivering AI products and services - Free to apply and fully remote - Takes just 5–10 minutes to apply - Individuals and companies can participate Applications are now open. Apply or nominate via the link in comments.
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Qi Li liked thisQi Li liked thisI��m thrilled to share that I’ll be presenting at Dreamforce 2026 for the very first time! Join me and Sujit R for our session: Trust at Scale: Agentic Observability for Tableau 📅 September 17, 2026 🕘 9:00 AM - 10:00 AM 📍 InterCon, L4, Nob Hill As AI agents become more powerful and embedded into everyday analytics workflows, observability becomes essential for building trust, transparency, and scale. In this session, we’ll dive into how agentic observability can help teams understand, monitor, and improve AI-driven experiences in Tableau. This is a special milestone for me: my first Dreamforce as a speaker. I’m excited, grateful, and looking forward to connecting with the Salesforce, Tableau, and AI community. If you’ll be at Dreamforce, I’d love to see you there! #DF26 #Dreamforce #Salesforce #Tableau #AgenticAI #Observability #AI #TrustAtScale #DataCloud #TableauCloud
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Qi Li liked thisThank you, Confluent, for the recognition! It’s been an amazing experience contributing to the Apache Flink and Apache Kafka communities. I’ve learned so much—not only from serving on the program committees for Kafka Summit, Current, and Flink Forward, but also from reviewing innovative and impactful proposals, meeting people from around the world, and working together to shape what stream processing looks like in the industry today. I’m grateful to be part of this incredible community and excited about what we’ll build together next!Qi Li liked this🌟 Meet our Catalyst of the Week, Jiangjie Qin! Jiangjie has been an incredible part of the streaming community for over 10 years, contributing to both Apache Kafka® and Apache Flink® and helping shape their ecosystems through ongoing technical contributions. Beyond his development work, Jiangjie regularly shares his expertise through conference talks and has served multiple times on the Program Committees for Kafka Summit, Current, and Flink Forward. Thanks for everything you do for the community, Jiangjie! 🙌 Learn more about our Catalyst program: https://cnfl.io/3P50GGo
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Qi Li liked thisQi Li liked thisHello everyone! If you're attending the Ai4 - Artificial Intelligence Conferences next week, I'd love to connect. I'm looking to learn how other organizations are approaching: - Agent orchestration, including context and memory management - Enterprise context layers, such as Context Lakehouse and similar architectures - Agent security, identity, and data access management - AI governance – How are organizations ensuring AI agents only access trusted, governed data? - Enterprise AI operating models for scaling AI across the organization If you're working on any of these topics, let's connect during the conference!
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Qi Li liked thisQi Li liked thisThrilled to share that Salesforce placed #6 on The Wall Street Journal's "Best Companies For the Future" list. As WSJ’s Alan Murray put it in introducing the list, “Retooling the corporation for a world of accelerating change is the existential challenge all now face.” Here’s what the ranking measured: AI readiness, innovation, talent, financial fitness, resilience, and agility. In the year we crossed $1B in Agentforce ARR, launched Headless 360, and processed 28.6 trillion tokens for our customers, the WSJ confirmed what we’ve known for 27 years: we are a company built for the future. Congratulations to the 500 companies recognized on this list. And thank you to every member of the Salesforce Ohana, every Trailblazer, and every customer. The future belongs to the builders, and we’re just getting started. https://lnkd.in/eSVScdHe
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Sanchit Narula
The best advice I got on my promotions as a software engineer was from a Principal Architect at Amazon after he told me his story of getting promoted to Principal, and this has stayed with me my whole career. He said, very simply: > Your architecture can be a love letter to your technical brilliance, > but if it does not move customer and company goals, it will not move your level. That hurt a little. Because I recognised myself in it. A few years ago I wanted to design something with every shiny thing in the book: API Gateway, Lambda, DynamoDB, event bus, the works. On paper it was beautiful. In reality it was expensive, slow to ship, and did not match the skills of the team that would maintain it. So we shipped a hybrid architecture instead. Fewer moving parts, more reuse of existing services, cheaper to run, easier to hand over. Over time, here is how my thinking about promotions changed. 1. Start from the business goal, not the tech stack Before talking about Kafka vs SQS or MySQL vs DynamoDB, answer this first: What money, risk, or customer pain will this remove? Promotions track that, not the number of services in your diagram. 2. Ship finished products, not clever demos Leaders remember the feature that went live, stayed stable, and earned or saved real money. Drive the entire lifecycle yourself: design, build, launch, oncall, cleanup, docs. 3. Make the team faster, not just yourself Tools, scripts, templates, better CI, better dashboards. If people quietly say “things move faster when you are on this” your manager already has half a promotion case. 4. Do your share of the unsexy work Oncall, migrations, bugs, incident reviews. Senior folks who avoid this slow the entire org. Senior folks who lean into it become trusted very quickly. 5. Grow people, not just systems Mentor juniors, run design reviews, write clear docs, set standards. When your manager sees that you are already acting like the next level, formal promotion becomes a catch up, not a favour. 6. Be proactive about your promotion, not obsessed with it Have periodic one to ones. Talk about where you want to go and ask what evidence your manager would need to support that. Remember your manager has ten other people to manage. It is your responsibility to make your impact visible. Do not be desperate. Understand the timelines and work within them. As you get close to the boundary, collect the missing data points: impact metrics, incident write ups, design docs, peer feedback. Make the story easy to tell. Most importantly, work for the business, not for promotion-driven development. If your roadmap only exists to tick boxes on a promotion rubric, people can feel it. If your roadmap clearly creates value, saves cost, or reduces risk, promotion becomes the natural side effect. So instead of asking “What new tech can I use this year?” Ask, “Where can I create obvious business impact and leave the system and the people around me better than I found them?”
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