Cost Estimation Manager in New York

As a Product Manager – IaC Detection, you will define, build, and launch capabilities that proactively detect infrastructure issues in code (e.g. Terraform, Helm) before they can be deployed into production and escalate into production incidents. The Infrastructure Monitoring team has pioneered shift-left detection in the industry with Bits Infrastructure Operations , and we’re looking for a Product Manager to expand this capability to a broader set of use cases Customers (and thus developers) are increasingly standardizing on IaC tools to deploy and maintain ever-growing infrastructure in the cloud. At the same time, SREs and Infra teams struggle with an increasing number of production incidents. By shifting-left and identifying high-impact infra changes before they are deployed, we help reduce production incidents, reduce waste, and free up SRE time to focus on value-added tasks. You will own the roadmap to expand IaC detection to a broader set of use cases, including cost detection, blast radius impact, as well as configuration changes on infrastructure powering applications like nginx, postgres and more. You’ll partner closely with Engineering, Design, and customers to build and iterate on the roadmap, build product market fit, drive customer adoption (including internal usage), and focus on coverage and correctness of the AI system. This is an opportunity to lead an initiative at the intersection of AI, infrastructure operations, and autonomous observability. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the product roadmap for IaC Detection, enabling customers to proactively detect and catch high-impact infrastructure and configuration changes before they are deployed into production and escalate into incidents. Define the end-to

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Storage Services team operates Pinterest's scalable online structured data storage platform—supporting both SQL-based table models and complex graph data structures—managing 100TB+ datasets and serving over 1.5M queries per second across many of Pinterest's most important products. We're looking for an exceptional Staff Software Engineer to lead the technical strategy and execution of our storage infrastructure initiatives, defining how these systems are designed, built, and operated. You'll drive innovation across distributed SQL, high-throughput/low-latency query processing, graph workloads, and the developer experience for storage clients. What you’ll do: Provide technical guidance and direction to a high-performing team building reliable, performant, and cost-efficient storage systems that operate at massive scale and power busines

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Observe by Snowflake is a high-growth SaaS observability platform built on the Snowflake AI Data Cloud, enabling businesses to troubleshoot modern distributed applications 10x faster. Now, as a core part of Snowflake, we’ve reached a major milestone in the evolution of the Snowflake platform. By bringing AI-powered observability directly into the Snowflake ecosystem, we’ve created the first truly unified platform for telemetry and business data. We’re looking for a Technical Account Manager to partner with our most strategic enterprise customers and ensure they derive sustained operational value from Observe. This is a hands-on, post-sales technical role focused on long-term platform adoption, optimization, and technical partnership. You will work directly with SRE, DevOps, platform, and engineering teams to embed Observe into daily workflows, evolve telemetry strategy over time, and continuously improve reliability, performance, and cost efficiency. This role is ideal for an experienced observability practitioner who enjoys being deeply embedded with customer teams, solving real production challenges, and acting as a trusted technical advisor in complex enterprise environments. What You’ll Do Serve as the primary technical owner and trusted advisor for assigned strategic a

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for business operations managers to join the team. This person will work closely with folks across marketing, sales, operations, and finance across a variety of initiatives to help scale the business in our next phase of growth. You'll be a generalist who gets in the weeds on all the business and operational aspects of a high-growth startup. In this role, you will: Drive in-depth quantitative analyses to inform our pricing and packaging strategy. Help spin up our deal desk and streamline enterprise deals. Support the exec team on various finance functions, from investor relations to large cloud vendor negotiations to identifying cost optimization opportunities. Implement new tools and processes to enable the GTM org to grow rapidly. Get creative on a spectrum of ad-hoc projects like securing new office space in Manhattan. Requirements: We are looking

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the role Ramp already serves thousands of organizations in industries where financial operations work differently: construction companies that manage spend by job and cost code, nonprofits that report by fund and grant, and public-sector organizations accountable for every taxpayer dollar. We are hiring a Lead Product Marketing Manager, Verticals to turn those differences into a durable growth advantage. You will own Ramp's vertical GTM operating model, beginning with Construction / A&E and Nonprofits / Public Sector. You will decide where Ramp should invest, become the resident expert on how finance works in those markets, influence the product roadmap, and build the cross-product narratives and motions that help Ramp win. This is not a content-only, campaign-only, or sales-enablement role. You will own the full vertical business read: market choice, ICP, product readiness, positioning, pipeline, win rate, activation, adoption, attach, campaign performance, and the next product or GTM intervention. What you'll do Set the vertical portfoli

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist . The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness. This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage. What You’ll Do Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost. Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers. Create and maintain solution architecture artifacts: System context and data flow diagrams Integration plan across Ramp and customer systems Security model covering permissions, access patterns, and au

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: Join a team that builds robust, real-time distributed systems for a cutting-edge database. We care about performance, reliability, scalability, and most of all learning and having fun together. Whether you’re a seasoned coder or just getting started, if you’re passionate about technology and eager to learn, you’ll fit right in. Who we are: We show up to work, ready to collaborate and build technologies that make a difference, with people who genuinely care. We chase improvements such as tail latencies, bytes throughput, cache hit rate, and operational cost efficiency. We believe learning is ongoing and that even the most complex problems can have simple solutions. What You’ll Do: Collaborate with teammates to design and build database features that power AI applications. Learn how to tune performance and support reliability in distributed systems (don’t worry, we’ll guide you). Help Pinecone run smoothly on popular cloud providers. Take ownership of your work and grow your skills every day. Have fun. Who You Are: 5+ years of work experience - programming in Rust, Go, C++, or a comparable language. You’re genuinely curious about distributed systems and eager to dive deep into technical challenges. You approach problems with creativity and persistence, and you’re comfortable asking thoughtful questions or seeking feedback. You’re excited to learn, value constructive feedback, and appreciate mentorship. Bonus Points: You have hands-on experience with cloud platforms (AWS, GCP, Azure) or have demonstrated an ability to pick u

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models. What You’ll Do Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform. Build tools that improve the agility and data experience of Ramp's Applied Scientists, AI Engineers, and Risk Engineers. Collaborate with stakeholder teams on building and productionizing machine learning applications. Build reliable, scalable, maintainable, and cost-efficient systems across the stack. What You Need Experience with workflow orchestrators like Airflow, Dagster, or Prefect. Experience building infrast

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The FinOps function is responsible for financial accountability, visibility, and optimization across all engineering-related spend at Plaid. This includes cloud infrastructure, AI/ML and data workloads, third-party SaaS tools, and other technical investments that support Plaid’s products and internal platforms. The team operates at the intersection of Engineering, Product, and Finance, ensuring that spending decisions are transparent, intentional, and aligned with product strategy and business priorities. Rather than functioning as a cost-control or approval layer, FinOps enables teams to understand, own, and optimize their spend while maintaining engineering velocity. Responsibilities Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities. Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks. Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans. Leads cost optimization initiatives, such as rightsizing, commitment strategies, an

We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team: As organizations rapidly invest in AI applications and build out AI labs, telemetry volumes are growing exponentially and costs are becoming unpredictable. From LLM interactions to agentic workflows, AI systems generate unpredictable streams of logs, driving up costs and making it harder to maintain efficient observability. These challenges are critical for organizations in regulated industries with strict data residency requirements, where data must remain within controlled environments. Datadog’s Bring Your Own Cloud (BYOC) team is reimagining what observability and security look like at petabyte scale in the AI era. The Opportunity: The Group Product Manager - Bring Your Own Cloud (BYOC) role is responsible for defining and bringing to market the next generation of telemetry analytics and insights capabilities in an AI-first environment. This role is highly technical and creative in nature as you will envision novel ways to enable customers to cost-effectively explore, analyze and report over petabytes of data through a welcoming and easy-to-use interface. You will partner with various teams to take advantage of BitsAI capabilities and surface critical insights on volume usage and retention for popular use cases. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and grow a team

Role Summary: Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines with log management software that customers deploy and manage in their own infrastructure. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Make customer-controlled deployments feel like a managed Datadog product: deployment, upgrades, configuration, observability, diagnostics, reliability, and secure operation across diverse customer cloud environments Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably that customers deploy and operate within their own cloud infrastructure. Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have significant experience building software that is installed, deployed, and operated in customer environments rather than only as a fully managed SaaS service. You have strong expertise in distributed systems,

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali