Technical Success Manager in New York

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 strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

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 strong engineers with experience building developer tools that users love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful interfaces that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python libraries with broad user-bases, ideally including some experience maintaining open-source software. Knowledge of advanced Python features, especially async programming. A strong product sense that manifests as a focus on developer ergonomics and productivity. A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our NYC or Stockholm office. Any of the following would be a plus:

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 a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

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 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 building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll have opportunities to build expertise in advanced performance techniques, including GPU/CUDA optimizations, kernel-level improvements, and model execution strategies for MoE and large-scale architectures. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, e

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. LEAD. STRATEGIZE. TRANSFORM. We are seeking an advanced professional handling complex enterprise AI/ML deployments, deconstructing system dependencies, and ensuring production robustness. WHY THIS ROLE? This role marks a shift from managing tactical tasks to managing strategic outcomes. You are a seasoned professional with a full understanding of your specialization, resolving a wide range of issues in creative ways. WHAT YOU'LL DO: Design robust, scalable AI/ML solutions utilizing the full Snowflake native stack and partner ecosystem. Perform deep-dive Root Cause Analysis (RCA) for complex system dependencies in AI/ML solutions. Collaborate cross-functionally with Sales and Product teams to align technical roadmaps with customer ROI. Mentor Level 3 architects on best practices for MLOps and architectural design. TECHNICAL DEPTH & RISK MANAGEMENT: Distributed Systems: Deconstruct failures in complex pipelines involving external cloud services (AWS/Azure/GCP). Predictive Failure Analysis: Critically think about potential failure modes like model drift and data skew early in the lifecycle. Governance: Architect data security and access controls specifically for sensitive AI/ML training data. SNOWFLAKE-NATIVE TECH STACK: Snowflake Model Registry, Cortex Functions, Python,

Datadog’s Implementation Services team helps customers implement and deploy Datadog quickly and successfully. Our team of architects leads the discovery, design, build, and launch of the Datadog platform to help customers accelerate time to value and get the most out of their investment. As a Senior Services Architect focused on Security and Cloud SIEM, you will help customers design, implement, and operationalize Datadog’s security capabilities across cloud, infrastructure, application, and log data sources. You will lead structured, outcome-driven professional services engagements delivered through a day-based professional services delivery model, partnering directly with customers through co-development working sessions, architecture workshops, implementation planning, and operational handoff. This role is ideal for someone who combines customer-facing consulting experience with strong cybersecurity knowledge, hands-on Cloud SIEM implementation skills, and an understanding of security control frameworks such as NIST 800-53, the NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. 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: Design and guide execution of Datadog implementations, focusing on Security and Cloud SIEM deployment, including discovery, requirements gathering, technical architecture, deployment planning, and launch. Partner with customers to map security requirements, controls, and monitoring objectives to Datadog capabilities, including frameworks such as NIST 800-53, NIST Cybersecurity Framework, CIS Controls, MITRE ATT&CK, SOC 2, PCI, HIPAA, ISO 27001, or similar standards. Advise customers on security data strategy, including log source prioritization, parsing, normalizat

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

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, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Qualifications 4-8 years of account management and sales experience. Customer empathy and deep desire to see customers succeed. Desire to get technical and the ability to learn the ins and outs of Plaid's APIs. Some familiarity in financial services and technical products; a high degree of intellectual curiosity. Excitement to work in a high-growth, ever-changing environment and to help build processes and tools as needed. Ability to work with all types of people and build long-lasting relationships. Strong Sales experience (negotiation/value-selling). Executive level communication skills - written and verbal. Relationship building (understand how to leverage internal/external executives, product, etc). Retention and Termination-save tactics. Responsibilities Own and manage the overall relationship with your portfolio of customers in our fastest growing customer segment. Build strong relationships with the C-Suite and Product teams to retain and grow revenue. Own and exceed revenue targets, which includes identifying and closing new upsell opportunities and leading commercial negotiations for contract renewals Help customers integrate and launch on Plaid. Solve complex customer ch

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 seeking experienced professionals with a strong background in Artificial Intelligence, Machine Learning, and Cloud Architecture to join our Services Delivery team to help create exciting new offerings and capabilities for our customers! In this strategic role, you will help customers expand their use of the Snowflake Data Cloud to bring AI/ML pipelines from ideation to full production. Leveraging Snowflake’s native features and extensive partner ecosystem, you will advise clients on best practices for scaling production-ready workloads. You will design tailored AI/ML solutions, coordinate closely with customer teams and Systems Integrators, and provide the technical leadership and oversight needed to ensure successful outcomes. AS A PRINCIPAL SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack. Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery. Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements. Work hands-on where neede

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 believe Plaid has the power to be the next-gen Credit Bureau - supporting large scale adoption of cash flow into the credit underwriting process. The Credit Decisioning platform team is responsible for building best-in-class cashflow based insights products that enable lenders to make more holistic lending decisions and empower broader access to Credit products for prospective borrowers. We own the systems and tooling that form the platform to build and serve these insights at huge scale, partnering with our Data partners to release new products yearly. You will be defining the future architecture of Credit insights products and executing against an ambitious product roadmap. You will partner with our Product, Data Science, and Machine Learning team to iterate on and productionize new insights that enable our customers to make more holistic lending decisions. Responsibilities: Leading technical architecture and execution across credit insights products: everything from data fetching and online feature serving for API requests, to offline production pipelines and tooling for model training. Scaling and evolving the architecture through an expected ~100x increase in load from deterministic factors

Join VTS as an Engineering Manager. As a technical leader, you'll drive high-impact, customer-facing projects across major features in web and mobile. You’ll play a pivotal role in advancing VTS's evolution into an AI-powered platform, further cementing our industry-leading position. In this role, you will be responsible for fostering a healthy and collaborative culture, guiding the team's execution and delivery, and mentoring engineers to grow their careers and capabilities. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** To thrive in this role, you have: Proven experience leading software teams using agile development methodologies. A strong technical background with a proven track record of building, deploying, and maintaining scalable web applications, services, and third-party integrations. Experience working on high-impact, business-critical domains, where reliability, performance, and operational stability are essential. Demonstrated ability to recruit and develop talent, strengthening the team's capabilities through effective coaching and mentorship. The ability to engage in strategic technical discussions, adeptly manage technical tradeoffs and risks, and ensure alignment with product and business goals, especially in environments involving multiple systems and external partners. A sense of empathy for the customer and a relentless focus on shipping high-quality products. Excellent communication skills that empower you to effectively convey ideas, coach, mentor, and educate others. A keen interest in building AI-backed features and leveraging AI as an engineering productivity tool. What you'll do: Lead and Develop a High-Performing Team : Foster a healthy, collaborative, and diverse culture that reflects our company and engineering values. Coach and mentor individual team members, creating a structured environment and feedback loop that supports career development and hi

Lithic is the modern card issuing and processing platform empowering ambitious financial companies to build the future of payments. Our infrastructure powers card programs for 100+ innovative clients, from fintechs reimagining credit and digital banking to platforms transforming disbursements and spend management. Companies like Mercury, Flex, and Novo rely on Lithic's developer-friendly APIs, direct network connections, and flawless reconciliation to launch and scale card programs in weeks, not years. We're building a future where access to better financial products materially improves people's lives, free from the constraints of 30-year-old mainframes and legacy processors. We're proud to be backed by world-class investors who share that vision, including Bessemer Venture Partners, Index Ventures, Spark Capital, Stripes, and Mastercard, along with many others. We're a team of 170+ across 26 states and 7 countries, headquartered in New York City. We are seeking a Product Delivery Specialist to join Lithic’s team in our NYC office. In this role, you will lead complex customer implementations, drive operational excellence, and develop scalable processes that enable billions in transactions for the most innovative fintechs and digital banks. This position offers a unique vantage point across our business from product and engineering to compliance and operations allowing you to tackle meaningful challenges while making a tangible impact. In this role, you will coordinate a wide range of activities from implementing customer requirements and configuring the software to conducting technical setup and integration support with the ultimate goal of getting the customer’s solution live as quickly as possible, driving fast Time to Revenue (TTR) and provide great customer experience. You will operate at the intersection of our customers, internal teams, and third-party partners, executing progress across multiple project streams simultaneously. You will launch new

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