Strategic Ai Adoption Lead Jobs

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n

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. As a member of Ramp's Risk Strategy & Operations team, you will leverage data to develop and optimize credit strategies. Credit is one of Ramp's most consequential products. Every policy change affects how customers can grow their usage, and how responsibly Ramp scales up while managing risk. Credit Risk Strategy owns these tradeoffs end to end. In this role, you will own or help build strategy across credit risk areas like credit limits, payment speed, and collections. You'll take ambiguous problems, get to the data, prototype the solution, and push the change with Product, Engineering, Data Science, Risk Operations, Finance, Customer Experience, and Compliance. AI fluency is required. We use AI as a core pillar of our risk management stack, and you will be prototyping and managing related Agents and tools. You should already be using tools like Claude Code, Codex, or similar AI tools to write code, explore data, prototype apps, automate workflows, and check your own work. You do not need to be a software engineer, but you do need to use AI to

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 Onboarding team owns the product flows and platform that powers all new customer account creation at Ramp. This includes Ramp's application decisioning system that interfaces with our fraud, compliance, and credit underwriting models. As an engineer here, you’ll own workstreams that expand Ramp's total serviceable market and improve the end-to-end customer onboarding experience. You’ll partner with product, data, and design, and work directly with stakeholders across sales, marketing, risk strategy, operations, and finance to accelerate Ramp’s growth. This role offers the opportunity to have an outsized impact on Ramp’s overall growth trajectory. What You’ll Do Build software to grow Ramp to its next millions of users Scale the output of our application decisioning ops team through automation and AI assistance Drive business outcomes through metric-driven software development Own the customer journey from discovering and applying to Ramp through getting approved for and onboarding to the product What You Need Minimum of 2 years of

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. As Ramp’s founding Privacy engineer, you will build a privacy program that powers Ramp’s growth while earning trust from customers and prospects. What You’ll Do Build privacy-focused application primitives and integrate them into our existing products Partner with other engineering teams to design and deploy solutions which are inherently privacy-centric and secure Improve, implement, and deploy data retention and anonymization strategies across our environment Track shifting legal standards (alongside with Ramp’s Privacy Counsel) and update Ramp systems and processes to match What You Need Minimum of 4 years of experience building software Minimum of 2 years of experienced focused on platform, privacy, and/or security Desire to work in a fast-paced environment, continuously grow, and master your craft Ability to turn business and product ideas into engineering solutions Nice-to-Haves Working knowledge of data-protection legal requirements Experience with Python (Flask), React, and AWS (ECS, as well as other core services) Benefits available to all

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: Join our Site Reliability Engineering team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Site Reliability Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking SREs who are passionate about building and maintaining resilient systems at scale. Your mission will be to design and implement robust monitoring solutions, automate operational tasks, and continuously improve our infrastructure's reliability and performance. You will: Design and Implement Observability Solutions : Develop comprehensive monitoring and alerting systems using modern observability tools. Create dashboards and metrics that provide real-time visibility into system health and performance. Implement logging strategies that enable quick problem identification and resolution. Drive Automation and Infrastructure as Code : Architect and implement infrastructure automation solutions using tools like Terraform, Ansible, or Pulumi. Design and maintain CI/CD pipelines that enable reliable and consistent deployments. Create self-healing systems that can automatically respond to common failure scenarios. Establish SLOs and SLIs : Work with product and engineering teams to define and implement Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Build systems to track and report on these metrics, ensuring we maintain high reliability standards while balancing innovation speed. Incident Management and Response : Lead incident response efforts, conducting thorough post-morte

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role: Join our Infrastructure Engineering team and help ensure the reliability, scalability, and performance of Replit's infrastructure that serves millions of developers worldwide. As a Staff Infrastructure Engineer, you will bridge the gap between development and operations, implementing automation and establishing best practices that enable our platform to scale efficiently while maintaining high availability. We are seeking Staff Infrastructure Engineers who are passionate about building and maintaining resilient systems at scale. Your mission will be to proactively find and analyze reliability problems across our stack, then design and implement software and systems to create step-function improvements. You will design robust monitoring solutions, automate operational tasks, and continuously improve our infrastructure's reliability, all while mentoring and educating the broader engineering team to make reliability a core value at Replit. You Will: Drive Automation and Infrastructure as Code: Architect, build, and improve automation to eliminate toil and operational work. Design and maintain CI/CD pipelines and infrastructure automation using tools like Terraform or Pulumi. Create self-healing systems that can automatically respond to common failure scenarios. Optimize Performance and Infrastructure: Collaborate with core infrastructure and product teams to performance tune and optimize our cloud deployments (Kubernetes, Docker, GCP). Identify and resolve performance bottlenecks, implement capacity planning strategies, and reduce latency across global regions. Elevate Developer Experience: Design and implement improvements to our build, test, and deployment systems to make software delivery faster, safer,

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. We are looking for a Security Operations Lead (SOC Lead) to build, mature, and operate our 24/7 detection and response capabilities across a modern cloud-native and AI-driven environment. This role leads the global SOC function—monitoring, SIEM ownership, detection engineering, alert triage, and operational readiness—while also evaluating and integrating emerging AI-based SOC products and autonomous response platforms . You will oversee monitoring across multi-cloud environments (GCP primary, AWS/Azure secondary), Kubernetes, SaaS services, endpoints, developer tools, and AI workloads . You’ll collaborate closely with Cloud Security, Compliance/GRC, SRE, Platform Engineering, IT/Endpoint teams, and AI Infrastructure to ensure our detection strategy scales and stays ahead of evolving threats. This is a hands-on leadership role perfect for someone who wants to shape the SOC of the future while solving complex challenges in a high-scale AI setting. What You’ll Do SOC Leadership & 24/7 Monitoring Lead, mentor, and scale a global SOC team responsible for 24/7 monitoring, alert intake, triage, correlation, and escalation. Build operational rigor: processes, runbooks, SLAs, metrics, and quality standards for high-scale environments. Cover monitoring across: Cloud infrastructure (GCP, AWS, Azure) Kubernetes/GKE/EKS/AKS clusters SaaS platforms (Google Workspace, GitHub, Slack, Okta, etc.) Endpoints (macOS, Linux, Windows) including EDR/XDR telemetry Developer platforms + CI/CD pipelines AI/ML systems and model-serving workflows AI-Based SOC Integration & Innovation Evaluate, adopt, and integrate AI-native SOC technologies for triaging, detection, and correlation Identify opportunities to automate triage, investigations,

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 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. We are the first line of defense against fraud and abuse on the Plaid platform. Our mission is to ensure the safety and integrity of our platform for consumers and customers. As a Fraud and Abuse Operations Analyst , you will be responsible for responding to fraud and abuse events, investigating claims, and triaging incidents. We also partner with product and engineering teams to inform and improve fraud mitigation strategies. Responsibilities: Safeguard Plaid's Platform: Participate in the abuse on-call rotation, directly protecting our users and customers by responding to and resolving fraud and abuse events. Your timely actions will be instrumental in maintaining trust and security. Drive Investigations and Mitigate Risks: Investigate fraud and abuse claims from diverse sources, partnering with senior teammates on complex cases. Your findings will inform decisions and strategies, directly impacting Plaid's ability to prevent future incidents and minimize financial losses. Proactively perform threat modeling of abuse surfaces and continuously survey external fraud trends, adversary techniques, tooling, and emerging threat vectors Support Incident Response: Help triage and manage fraud and abuse ev

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. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownershi

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. We are the Data Foundation & AI team within Plaid’s Data organization. Our mission is to build the shared ML and AI infrastructure that powers intelligent capabilities across Plaid’s product suite. We develop the foundational systems, models, and data assets that transform Plaid’s unique financial network data into scalable, general-purpose representations that teams across the company can leverage. Our work spans the full ML lifecycle — from large-scale data curation and model pretraining to production serving, evaluation, and monitoring. As part of the team, you’ll work at the intersection of machine learning infrastructure, applied AI, and distributed systems, helping establish the core AI platform that enables innovation across Plaid. As a Staff Machine Learning Engineer, you will lead the technical strategy and development of Plaid’s foundation models, driving key decisions across pretraining objectives, model architecture, and fine-tuning approaches that power a wide range of downstream product applications. You will serve as the technical lead for the full machine learning lifecycle, overseeing everything from data curation and experimentation to production deployment, feature management,

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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 technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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 technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

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. Snowflake are looking for a Senior Solution Engineer for the UK market who can solve our customer’s most complex problems. In this role you will work directly with the account sales team and channel partners to understand the needs of our customers, strategize on how to best support them in their evaluation and ultimately help our customers choose Snowflake as their solution. As a Snowflake Solution Engineer you share our passion for solving complex data challenges and helping organizations to get the most out of their data assets. Our technical landscape is ever evolving and you are keen to learn new skills and put them into practice on real world challenges. You are able to translate features and functions into solutions that solve business problems, in conversations with technical or business teams, with end users or executives. In this role you will get to: Present Snowflake’s technology and vision to executives and technical contributors at prospects and customers Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation Create and develop technical champions in your accounts to drive deals and achieve a technical win Be at the cuttin