Technical Architect in New York

Datadog’s Technical Solutions organization includes 1,200+ sales engineers, support engineers, post-sales experts, and solution architects. They run on an ecosystem of enterprise platforms and internal tools that directly shape how we serve customers. Technical Solutions Operations (“TSO”) owns that ecosystem. We manage the full lifecycle of the systems TS depends on: Zendesk, Jira, Confluence, and a growing portfolio of off-the-shelf and purpose-built tools. We do the work to operate, maintain, and evolve the platforms powering daily workflows across TS. When a vendor tool reaches its limits, we extend it through customization, integration, or targeted solution development, tapping internal partners across Datadog as needed. We’re looking for a Systems Engineer who wants to own enterprise platforms end-to-end. You go from understanding the business process, to designing the right solution (whether that’s configuration, integration, or code), to measuring whether it actually moved the needle. 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: Own enterprise systems through their full lifecycle. You’ll be the technical owner for one or more platforms that TS relies on daily. That means understanding how the system is used, where it’s falling short, what’s coming from the vendor roadmap, and what needs to change. You drive improvements from assessment through implementation. Engineer solutions that create leverage. Not every problem is solved by configuration. You’ll build and evolve enterprise systems, integrations, automations, and internal tools that multiply the effectiveness of 1,200+ technical experts. Where AI can make a solution smarter (e.g., intelligent routing, automated triage, agent-assisted workflows), you'll include AI in the initial design, no

TPMs at Datadog see the problems hiding between teams, engineer away the work that shouldn’t require humans, and drive the company’s most technically complex and consequential bets to completion. About the Role Technical Program Management at Datadog operates at the intersection of engineering depth and organizational reach by driving high priority, cross-functional programs that are too complex and consequential for any single team to own. We partner with engineering on solving deeply technical problems at scale by connecting the people, decisions, and context to move Datadog's most important work forward. We build the systems and automation that make entire classes of program work self-executing. We are in the architecture conversation early, earning trust through technical judgment. We use AI to surface risks earlier, accelerate program execution plans, and find cross-team patterns that would otherwise stay hidden. The faster teams move, the more essential it is to have someone who can operate across them. What we expect These are the expectations we hold for every TPM at Datadog. Technical depth, product domain expertise, and AI systems literacy; knowing how AI solutions work, where they fail, and the scope and impact of those failures. AI brings more complexity into the picture - the technical bar is higher, not lower. Build the systems that reduce the need for coordination Identify what matters before anyone asks, and automate the rest Engineer program lifecycles end-to-end See what no single team can see and own the solution Drive the company's most technically complex and consequential bets through cross-functional agreement, organizational visibility, and influence Build AI powered automation tools and deploy them at every stage of program execution What you will do See Across: Identify What No Single Team Can See Own large cross-functional programs spanning multiple engineering orgs, product, and business functions Proactively surface systemic risks, cross

About DataCamp DataCamp's mission is to empower everyone with the data and AI skills essential for 21st-century success. By providing practical, engaging learning experiences, DataCamp equips learners and organizations of all sizes to harness the power of data and AI. As a trusted partner to over 20 million learners and 6,000+ companies , including 80% of the Fortune 1000, DataCamp is leading the charge in addressing the critical data and AI skills shortage. About the role + Responsibilities The Learning Solutions Architect is a customer-facing technical trainer who helps organizations build data and AI capabilities with DataCamp. You’ll deliver engaging live training (virtual and onsite) and create tailored learning materials on the DataCamp platform—think custom courses, projects, certifications and assessments that map to each customer’s roles, tools, and outcomes. You’ll partner with Customer Success, Sales, Product and Content to scope blended learning paths, teach high-impact sessions, and publish reusable, high-quality content that accelerates adoption and measurable skill uplift for some of our most high-value customers. Qualifications Loves to teach. Comfortable spending multiple hours weekly in front of a virtual or onsite classroom. 2+ years in technical training, data science/analytics education, solutions engineering, or similar instructor roles. Broad technical range across AI, Python/SQL/R and Power BI/Tableau; familiarity with Databricks/Snowflake is a plus. Learns new tools quickly; enjoys tailoring content to different personas (analyst, engineer, business user, exec). Strong communicator who can simplify complex topics for technical and non-technical audiences. Detail-oriented and process-driven; delivers sessions and materials with substance. Flexible schedule to support time zones (this is not a 9 to 5); occasional travel for onsite delivery. Some of your key metrics will be: Customer satisfaction: survey, engagement, repeat bookings Profe

TPMs at Datadog see the problems hiding between teams, engineer away the work that shouldn’t require humans, and drive the company’s most technically complex and consequential bets to completion. Technical Program Management at Datadog operates at the intersection of engineering depth and organizational reach by driving high priority, cross-functional programs that are too complex and consequential for any single team to own. We partner with engineering on solving deeply technical problems at scale by connecting the people, decisions, and context to move Datadog's most important work forward. We build the systems and automation that make entire classes of program work self-executing. We are in the architecture conversation early, earning trust through technical judgment. We use AI to surface risks earlier, accelerate program execution plans, and find cross-team patterns that would otherwise stay hidden. The faster teams move, the more essential it is to have someone who can operate across them. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What We Expect: These are the expectations we hold for every TPM at Datadog. Technical depth, product domain expertise, and AI systems literacy; knowing how AI solutions work, where they fail, and the scope and impact of those failures. AI brings more complexity into the picture - the technical bar is higher, not lower. Build the systems that reduce the need for coordination Identify what matters before anyone asks, and automate the rest Engineer program lifecycles end-to-end See what no single team can see and own the solution Drive the company's most technically complex and consequential bets through cross-functional agreement, organizational visibility, and influence Build AI powered automation tools and

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospect

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: As a Forward Deployed Architect on Notion’s Services team, you will help customers turn AI ambition into operational reality and unlock the full potential of our platform. You will partner directly with customers to design, build, and launch AI-native workflows that drive adoption, usage, and measurable business outcomes. This role sits at the center of Notion’s workflow-led GTM motion. You will partner directly with customers to understand their business goals, operating processes, technical environment, governance needs, and adoption barriers, then translate that context into scalable Notion architectures that drive measurable value. You will be hands-on across discovery, solution design, workspace architecture, workflow build, AI implementation, launch planning, adoption and handoff. You will work deeply with customers to define what Notion should own, where it should integrate with existing systems, and how Notion can become a durable operating layer for their teams. The best candidates combine strong consultative discovery, systems thinking, technical fluency, AI-native workflow design, implementation judgment an

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. Our Solution Engineering organization is seeking an AI Specialist who can provide hands-on expertise and support while working with technical decision makers and data scientists to design and architect AI solutions built on the Snowflake AI Data Cloud. This is a strategic role that works closely with cross-functional teams, including product, engineering, and the broader field organization to ensure successful execution and customer adoption of Snowflake’s AI & ML solutions. IN THIS ROLE YOU WILL GET TO: Be the technical expert in the room that positions Snowflake’s AI and ML features and value to technical stakeholders at Snowflake’s customers across the Americas. Partner with Snowflake account team teams and customer champions to scope and drive POCs to success and technical wins that prove the value of Snowflake’s capabilities, including executive readouts and business value cases. Collaborate with Snowflake’s product and engineering teams to influence Snowflake’s AI and ML roadmaps based on customer feedback. Publish content that helps the team and company scale beyond your individual efforts, like blog posts, presentations at conferences, or technical collateral like notebooks and demos. Influence, tailor and maintain Sales Engineering AI and ML selling assets, inc

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: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

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 are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

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

About the Team DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. The Marketing Technology team is responsible for delivering best-in-class tools, data, and processes so teams at DoorDash can effectively acquire new customers, drive retention, and grow new business lines across all our audiences. Our mission is to enable teams to deliver personalized, engaging, and relevant content across all our owned and paid channels. We partner closely with Product, Engineering, Data Science, and Analytics teams to translate Marketing’s technology needs into measurable business outcomes for our Growth and Performance Marketing teams. About the Role We're looking for a Senior Associate, AI Solutions Architect to help build and scale AI-powered tools across DoorDash's Marketing teams. You'll work alongside our existing Marketing Technology AI Solutions Architects to identify opportunities where AI can solve real marketing problems, then build, test, and iterate on the solutions that make it happen. This role is grounded in hands-on building: you'll spend your time prototyping, coding, and shipping tools rather than pitching strategy from the sidelines. This is a great opportunity to grow your technical and strategic skills at the intersection of marketing and AI. You'll get mentorship from a team of builders and exposure to the full lifecycle of AI development from prototype to deployment. This role will report to the Senior Manager, Marketing Technology within the Growth Marketing organization. You're excited about this opportunity because you will… Build and deploy AI-powered tools and automations, such as automated reporting, QA frameworks, and workflow optimizations. Develop MVPs and proof-of-concepts, then iterate based on user feedback within a defined w

About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. Own the quality and impact of the team’s work across solution design, implementation, production readiness, adop

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

The Team We are Datadog’s in-house product experts. The Technical Solutions team enables Datadog’s worldwide growth by educating potential partners and ensuring that our integration ecosystem is high-performing, secure, and valuable. Partner Technology Solutions Engineers (TSEs) are the technical bridge between Datadog and our third-party developer community. We act as consultants, helping partners build world-class monitoring solutions on the Integration Developer Platform (IDP) . The Opportunity Datadog is looking for a Partner Technology Solutions Engineer to join our fast-paced team. You will be the primary technical contact for our partners, guiding them through the entire integration lifecycle—from initial architectural design to final publication on the Datadog Marketplace. This is a unique role that combines deep technical troubleshooting with high-level consulting and platform advocacy. You will work directly with external developers and see your contributions immediately reflected in the Datadog ecosystem. You Will Act as the technical lead for partners, advising on OAuth flows, log pipelines, OpenTelemetry, and agent-based vs. API-based configurations Perform architectural assessments and deep-dive code reviews for partner integrations in the integrations-extras and marketplace repositories, ensuring they meet our Quality Rubric Solve complex technical challenges for partners via Zendesk, Slack, and dedicated technical consultations Identify friction points in our Integration Developer Platform (IDP) and partner with our internal Product and Engineering teams to build a better developer experience Maintain public-facing developer documentation and internal tracking systems ( JIRA ) to ensure transparency and scale You Are A technical expert with 3+ years of experience in a technical role (Support Engineering, Solutions Architecture, or Software Development) Proficient in at least one language (Python or Go preferred) An observability enthusiast who unders