Lead Engineering Manager Core Performance in New York

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Delivery Engineer Team As a member of the Delivery Engineer team, you will own the post-sales onboarding and data health for customers. Your goal will be to drive data trust, help embed Mixpanel into our customers’ data stack, and deliver on emerging AI integrations — delivering on the full value of Mixpanel as a self-serve analytics platform. You will work and consult with GTM team members and a diverse array of customers to successfully roll out product analytics to their organization and execute on technical projects and services that delight our customers. About the Role As a Delivery Engineer II, you will be on the front lines with our clients as they integrate Mixpanel into their core product development processes. You will lay the foundation for customers to adopt product analytics and get value from Mixpanel by delivering a world-class, on-time, and value-oriented onboarding experience. With your comprehensive project management knowledge, consultative approach, expertise in the analytics space, and technical knowledge of the modern data stack, you will lead our clients' first experience with Mixpanel as they incorporate product analytics into their data ecosystem as a foundational element. With your deep technical breadth and expertise in the analytics space, you’ll be the expert consultant on all things data and ecosystem. As Mixpanel and our customers continue to iterate on agentic integrations, you’ll own ensuring customers are able to build, assemble context, and integrate AI workflows with Mixpanel. Responsibilities Own onboarding and data health for our strategic and high-value c

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

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. We are looking for a Senior Solution Engineer who thrives at the intersection of data, AI, and complex enterprise architecture. In this role you will work directly with the sales team and channel partners to understand the data challenges of our customers, strategize on how to navigate winning sales cycles, deliver compelling data-driven demonstrations, and support enterprise Proof of Concepts that showcase measurable business outcomes. As a Snowflake Solution Engineer you must share our passion for transforming how organizations use data — from raw ingestion to real-time analytics to AI-powered applications. You thrive in a dynamic environment, are equally comfortable whiteboarding a medallion architecture with a data engineering team and presenting data ROI to a C-suite, and you bring deep opinions about what good data platform design looks like. IN THIS ROLE YOU WILL GET TO: Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward Build and deliver tailored demos and proof of concepts across Snowfla

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. Today, CLEAR is well-known as a leader in digital and biometric identification, reducing friction for our members wherever an ID check is needed. We’re looking for a Senior Software Engineer to establish our Observability framework and foundations. You will join us to accelerate building and scaling our innovative systems that support our growing identity platform. You will drive on Observability best practices to find and fix gaps in our observability and our overall systems. You will also lead practices such as load testing, capacity planning, game days, chaos testing, and incident post-mortems. What You Will Do: Embed within the Engineering pillar to deeply understand the product and implement observability across all key flows Facilitate and build load testing cases, ensuring we understand the limits and scaling factors of our services and systems Contribute to observability and support the design of new services and systems, ensuring highly reliable and scalable concepts are implemented Build and lead practices such as game days, chaos engineering, and failure analysis Build long-term capacity plans, with an eye toward reliability and cost-efficiency Who You Are: 6+ experience writing production-grade software in a modern language, such as Java and Python. Strong knowledge of distributed systems concepts (think CAP theorem), microservices architecture, and distributed tracing . Experience with modern observability systems such as Datadog. Experience with performance debugging tools and patterns. You should be able to read a f

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 Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more — helping them design and ship production infrastructure on Modal's platform. The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will: Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal Lead technical discovery and architect

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

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Datadog is expanding the Technical Solutions (TS) organization by seeking a customer-focused, deeply technical Distinguished Architect to join our Product Solutions Architecture (PSA) team. In this role, you will act as a technical multiplier for the world's leading AI labs and AI-native companies. You will bridge the gap between their bleeding-edge infrastructure aspirations and Datadog’s technology roadmap, ensuring our platform natively solves the unique observability challenges of training and deploying foundational models 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: Leadership : Demonstrate thought leadership in the AI/LLM space. Influence key decision makers and stakeholders by connecting technical capabilities to organizational and business impact. Advisory : Strategically partner with highly technical Founders, Heads of Infrastructure, and Research Lead peers. Guide them on best practices and emerging industry trends in the AI/LLM space. Lead high-level technical and architectural conversations around AI adoption. Presentations : Lead deep-dive architecture reviews and design engagements with customer teams and their leaders to share industry trends, best practices, and demonstrate how Datadog can support high-throughput hyper scale AI workloads. GTM : Identify emerging AI-native technology shifts and feed them directly back to Datadog Product Management. Co-create custom observability integrations and solutions alongside Product SAs to keep Datadog at the absolute forefront of the AI stack. Collaboration : Collaborate with Product Solutions Architecture (PSA), Sales, Sales Engineering and Marketing in providing high-quality technical resources to a broad audience of practitioners and economic buyers. Hiring : Assis

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a Senior Product Security Engineer to serve as a technical leader and strategic contributor within our Product Security team. This role goes beyond execution — you will drive the evolution of CLEAR’s application security posture by influencing architecture, shaping security engineering processes, and mentoring team members in security and engineering. You’ll lead security initiatives across the organization and help embed security into every stage of our software development lifecycle. What you'll do: Drive security strategy and implementation across all CLEAR products and engineering teams, ensuring consistent protection of customer and business-critical assets. Partner with engineering leadership to align application security initiatives with company-wide technology and product roadmaps, balancing innovation with risk mitigation. Provide technical leadership across CLEAR’s application security initiatives, guiding architecture, design, and development to meet high security standards. Serve as a trusted advisor to cross-functional teams — including Engineering, DevOps, Product, GRC, and IT — enabling secure-by-design practices across the organization. Design and drive implementation of scalable automated security controls and testing frameworks integrated into CLEAR’s CI/CD pipelines. Lead complex threat modeling, architecture reviews, and risk assessments across high-value systems and platforms, driving meaningful security outcomes. Engage with CLEAR's customers to provide insight and support their fraud and ident

We’re looking for a Senior Staff Software Engineer with deep experience in GenAI/ML to join Datadog’s Application Performance Monitoring (APM) team. APM is a product which provides deep visibility into applications, enabling users to identify performance bottlenecks, troubleshoot issues, and optimize services. With distributed tracing, profiling, out-of-the-box dashboards, and seamless correlation with other telemetry data, Datadog APM provides some of the deepest and most structured visibility into the health and performance of applications. This context sets us up for an opportunity to be the world leaders in agentic investigations and incident troubleshooting. You’ll act as a technical leader within the APM group, focused on agentic workflows. You’ll lead efforts to design, train, evaluate, and deploy GenAI/ML models at scale. We’re looking for a product-minded ML engineer with strong technical expertise, excellent communication skills, and a track record of driving impactful initiatives end to end. 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: Serve as the technical owner for GenAI initiatives within APM, leading design, development, and deployment of ML/AI-powered features across multiple teams. Guide long-term strategy and technical direction for GenAI workflows across APM and related products. Build and benchmark GenAI/ML models using state-of-the-art techniques. Contribute to Datadog’s broader senior engineering community through thought leadership and collaboration on company-wide initiatives. Collaborate with cross-functional teams to build automated investigation and triaging tools. Influence product direction by bringing a strong product mindset to your work, always advocating for the end user. Guide teams through ambiguity, sc

A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. What you’ll do Develop and maintain the information security policy and standards library, aligning it with business priorities, regulatory expectations, and control objectives Lead independent assessments of the information security program, including regulatory examinations and third-party evaluations Identify technology risks across a complex business environment and drive mitigation aligned with our firm’s standards and control expectations Investigate data privacy inquiries and privacy-related events, assess business impact, and coordinate timely response activities Partner with technology, legal, compliance, and business stakeholders to translate risk findings into practical remediation plans Advise control owners on policy interpretation, risk treatment, and evidence expectations for assessments and examinations Prepare clear reports for management on team activity, emerging risks, remediation progress, and key decisions Maintain accurate risk, policy, priv

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Lead the technical design and architecture of major platform initiatives, author design documents and build consensus across engineering teams. Define technical roadmaps for complex, multi-quarter projects that span multiple teams. Make critical architectural decisions for company documentation infrastructure, balancing scalability, reliability, and developer experience. Evaluate and set direction for integrating emerging technologies, including AI/LLM capabilities, into company documentation platforms and authoring tools. Establish and evolve engineering standards, best practices and technical guidelines for the team and broader organization. Partner with engineering teams across the company to understand documentation needs and design integrated solutions. Design, build and maintain scalable, reliable and performant services and systems. Contribute high-quality code across the full stack and navigate codebases with different languages and tools. Debug and resolve complex production issues and improve system reliability. Take ownership of system health and incident response. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Software Engineering, Engineering, or a related field, plus four (4) years of experience in Software Engineering. Must have four (4) years of experience in each of the following: - Working in a full stack environment with a foc

What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity As a founding enterprise AE, you'll build the playbook for how we break into and grow enterprise accounts. You'll take deals from first conversation through close and expansion alongside our AI Strategist.You'll serve as the strategic advisor to the biggest and fastest growing companies in the world including Uber, Figma, Service Now, Snowflake and Rippling. Every deal cycle doubles as a product feedback loop and helps us make the product better, faster. The role grows with the company: keep growing as an IC with bigger accounts and bigger earnings, or step up to build and lead enterprise sales as we scale. What you'll own New enterprise logos. Net-new enterprise revenue, full cycle from first touch through close and expansion. You'll discover accounts through our powerful PLG engine or outbound into named accounts that are a great fit for us. Complex, multi-threaded deals. Get past the surface pain to the business problem underneath, then tie Mutiny's value to what actually moves the committee. Navigate buying committees from the CMO and VP of Sales down to the reps who'll use the product daily. Translate what Mutiny does into outcomes each stakeholder cares about. The story. Help buyers understand why Mutiny, why now, and what it means for their team. Partner with the CEO

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: Replit is redefining how software gets built — from solo developers to engineering teams at scale. As Director of Sales, you'll lead our enterprise sales motion and own the revenue engine that turns Replit's explosive product-led growth into durable, high-value contracts. You'll inherit a talented GTM team and take them to the next level. What You'll Do Lead, coach, and develop a team of GTM Executives — running weekly pipeline reviews, deal strategy sessions, and 1:1s that accelerate rep performance. Help shape the enterprise sales playbook: ICP, discovery frameworks, upsell and closing motions Own the full sales cycle on strategic deals — from first call to signed expansion — modeling what great looks like for the team Forecast accurately and report pipeline health, conversion metrics, and deal velocity to exec leadership weekly Represent Replit at key industry events and with high-value prospects where executive presence accelerates deals Required Skills & Experience 7+ years in B2B SaaS sales, with at least 3 years managing quota-carrying AE teams Proven track record closing enterprise deals ($100K+ ACV) and exceeding team quota Experience selling developer tools, infrastructure, or technical platforms — you understand the engineering buyer and can go deep on technical value props Data-driven operator: comfortable in Salesforce (or similar CRM), can build and own a forecast Sharp communicator — equally effective in a board-level business case and a hands-on demo with a skeptical CTO Bonus Qualifications Experience at a PLG-driven company (Figma, Notion, Linear, Vercel, etc.) with a motion that bridges product usage to enterprise contracts Familiarity with AI coding tools, cloud IDEs, or develope