Ai Agent Engineer With Copilot Studio And Power Platform in New York

Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog. 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 Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets) Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions) Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops Define how observability data and business data come together to serve unique use cases Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs Work on the product pricing Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools Who you are 5+ years of experience

Become a part of our caring community Help shape practical, responsible AI solutions that improve healthcare experiences and outcomes. Humana’s Enterprise AI organization develops safe, scalable AI solutions across our Insurance and CenterWell businesses. We bring together product managers, data scientists, engineers, policy experts, and business leaders to apply emerging technology to meaningful healthcare challenges. As Associate Director of Applied AI, you will lead teams that design, build, and deploy enterprise AI solutions, with a focus on generative AI and intelligent agents. You will connect technical strategy to business needs, guide responsible delivery in a regulated environment, and help teams turn promising ideas into measurable outcomes for members, patients, and associates. Key Responsibilities Lead and mentor teams developing production-ready AI solutions that improve healthcare delivery, member experiences, and business operations. Help define and execute the roadmap for applied AI initiatives in alignment with enterprise priorities and business needs. Guide the evaluation and adoption of machine learning, generative AI, large language models, multimodal models, and intelligent agent technologies. Oversee scalable APIs, frameworks, data pipelines, retrieval-augmented generation solutions, and agent orchestration capabilities. Partner with product, data science, engineering, architecture, security, and business teams to translate requirements into reliable solutions. Establish standards for AI evaluation, obse

Salary range: $300k - $350k | Equity: 0.4% - 0.6% | In-Person: NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, Chandra, Surya, Marker, and Lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for an engineering lead to guide our team while staying hands-on in the code. You'll set the technical direction and standards for how we build the interfaces, tools, and infrastructure behind our OCR, extraction, and document-understanding systems. This includes everything from optimizing agent loops and interfaces to helping to speed up inference. This is a player-coach role. You'll manage and grow a team of three engineers, own engineering delivery and quality, and spend a large share of your time writing code - focused on architecture, infrastructure, and the hard problems rather than routine feature work. You’ll partner closely with the research team to define the handoff between experimentation and production. As a small and fast-moving team, roles are fluid and ownership is high. You'll work directly with the founder to set priorities, ship features, and make our technology accessible to a global community of builders. Day to day, you will: Manage and grow a team of three engineers - 1:1s, prioritization, feedback, and hiring as we scale. Own engineering delivery, quality, and technical standards across code, testing, infrastruct

As a Senior Platform Product Manager focused on AI SDLC Trusted Throughput, you will define and drive the product strategy for enabling safe, reliable software delivery at AI-native scale across Datadog’s Internal Developer Platform. As AI accelerates development velocity and system complexity, you will help evolve SDLC systems from human-supervised workflows to platforms with built-in safety, observability, and correctness guarantees. You will partner closely with engineering, security, and developer platform teams to improve deployment reliability, operational visibility, and governance while enabling both engineers and AI agents to move quickly with confidence. This role offers the opportunity to shape foundational developer infrastructure and influence how AI-powered software delivery operates across Datadog. 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 the product strategy, roadmap, and execution for AI-native SDLC throughput and reliability initiatives across Datadog’s Internal Developer Platform Define and drive platform outcomes aligned to DORA metrics, balancing deployment velocity with reliability, change failure reduction, and operational safety Partner with engineering, infrastructure, security, and developer experience teams to build automated validation, auditability, and risk-scoring capabilities into deployment workflows Deliver actionable SDLC observability and diagnostic capabilities that connect executive-level metrics to operational signals across the software delivery lifecycle Drive systems that monitor and validate AI-generated or AI-attributed changes to ensure correctness, compliance, and trustworthy automation Serve as a cross-functional product leader across SDLC Foundations, Security Engineering, and compl

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. Feature flags used to be simple on/off switches. That's changing fast. Flags are becoming a control plane: they're tied to observability, they drive rollout decisions, and AI agents build and run more of this work every day. Datadog is building the platform for that future, and we are now expanding our Feature Flagging & Experimentation product to pair flag decisions directly with observability signals and to modernize the flagging workflow for an SDLC increasingly run by agents. As a Senior Product Manager for Feature Flagging, you will own product strategy and drive execution across flags-plus-observability integration and agentic-era flagging workflows. You will set direction for a critical area of the roadmap, work closely with the observability, RUM, and APM teams, and report directly to the Director of Product leading this team. You'll be relied on to make sound, independent product judgment calls with limited oversight, bring engineering credibility to every decision, and drive B2B go-to-market strategy alongside sales. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. This role is based in New York City and works from our office 3 days a week to support that collaboration. What you will Do: Find every place where a flag decision and an observability signal should talk to each other - rollout gating, anomaly-triggered rollback, experiment diagnostics - and ship a roadmap that unlocks observability and experimentation differentiators in Datadog Feature Flags

VP, Product Insurance underwriting runs on human judgment, manual workflows, and knowledge locked in someone's head. It breaks when that person leaves and doesn't scale when the book doubles. Sixfold is building AI agents that understand risk the way a 20-year veteran underwriter does. Not summaries or flags, but systems that make real decisions on billions in premium for some of the world's largest carriers. AI is the product, the workflow, and the moat. If you think in systems, move fluidly from research to pixels, and are energized by designing AI-native experiences where the best practices haven't been written yet — this role was made for you. Who We Are 🏔 Product: Sixfold is the AI brain for underwriting. Our platform handles submissions at scale, assessing risk against appetite, surfacing cited insights, and deploying AI agents to handle research, referrals, and triage so underwriters can focus on building profitable portfolios. 💪 Team: A focused team of insurance operators, AI researchers, and engineers who love hard problems. We've pushed the boundaries of what AI can do with unstructured data — from teaching AI to understand that a bakery in Florida faces different risks than one in Montana, to knowing when a manufacturing company's pivot from toys to medical devices fundamentally changes their risk profile. We ship fast and stay close to customers. 📈 Traction: Processing billions in premium for some of the world's largest carriers. We know AI. We know underwriting. We're building what comes next. About the Role You'll inherit a strong product and a capable team, but that's the starting point, not the job. The job is figuring out what underwriting becomes once AI stops assisting and starts deciding, and getting there faster than the market expects. You prototype to find out, not to perform speed. You're drawn to this problem because the underwriter of the future is one of the more interesting design problems in software right now. In this role, you will:

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As an Account Executive, Enterprise, you will own the complete sales process from start to finish. You’ll work closely with Marketing, Partner Managers, Sales Leadership, Sales Engineers, Account Management, Legal, and Finance to take a large-sized business prospect to an active Dialpad client. In addition, you’ll help

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali

The way products get built is changing. Agents write a growing share of shipped interfaces, designers work in code, and a design system's output is bigger than a component library. At Datadog we're redefining ours for that world, and evolving how the product looks and feels at the same time. DRUIDS is the design system behind every Datadog surface, used daily by more than a hundred designers and thousands of engineers across thirty-plus products. You'll lead the team that owns it: designers and design engineers who set the system's direction, hold the quality bar for what ships, and build the tools that make designing in code the default way to work. The team partners closely with product designers, frontend engineers and PMs across the company. This is a hands-on leadership role in a technical, engineering-forward company. You'll be expected to have a point of view and defend it, to be the person the design org asks about quality, and to make the call when work isn't good enough yet. Much of what a design system should be right now hasn't been settled — here or anywhere else. If you're a designer who never stopped making things, and you'd rather decide what a system should be than maintain one that already exists, this is the role. 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 team and set its direction Decide what DRUIDS owns, what it ships, and what stays with product teams. Own where the system goes next. Have a view on what a design system should be, and argue for it. Turn direction into a roadmap, and work with partners on what gets built and when. Coach the designers and design engineers on your team, be clear about what each person owns, and hire as the team grows. Own craft and quality Own the craft and quality of components, patterns,

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE We're looking for a Marketing Operations Manager who can own and harden the systems layer of Baseten's Marketing engine. Marketing at Baseten is scaling fast — more spend, more campaigns, more model launches, more inbound. The systems underneath (Our ESP, CRMs, forms, tracking, routing, alerting) need an owner who treats them like production infrastructure that cannot go down. When something breaks, it costs us time, pipeline, and trust in the data. This role exists so it doesn't break. You’ll simultaneously build for the future and re-think assumptions about our tech stack in the age of agents. This is an offensive play that gives the rest of the team leverage and superpowers to hit our ambitious goals. This is NOT an IT or service role. This is a core member of the marketing team who implements technology to achieve outcomes. RESPONSIBILTIES Own the marketing tech stack end-to-end: ad platforms, email systems, tracking, pixels, forms, connectors. Build defense-in-depth on inbound: spam/bot protection, rate limiting, email/domain validation, sync gating — and the alerting to catch anomalies before they hit sales or leadership dashboards. Enforce data integrity: UTM governance, campaign membership, lifecycle stages, lead scoring and routing logic, field-level hygiene, canonical metric definitions. Operationalize the web request pipeline with our dev agency: structured briefs, tickets, SLAs, and launch-day runb

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. 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 strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

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 We’re rolling out Go support at production scale at Notion, and we need an owner who can make it durable. You’ll lead the work to turn Go into a fully supported, well-operated platform: reliable and scalable service patterns, paved paths for our tooling stack, and the guardrails that make building in Go feel fast and safe. This role matters because our next wave of AI and agent-driven products will require backend services where Node won’t always be the right fit, and the platform decisions we make now will compound for years. While Go is the core focus, this role sits within Developer Experience and will regularly tackle other high-leverage engineering productivity challenges, developer experience ranging from AI-assisted development workflows and remote agent environments to CI performance, deployments, and reliability tooling. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days.

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

Business Systems drives efficiency across Datadog through business process analysis, systems automation and integrations, AI agent and MCP development, and vendor/software review. The team is increasingly embedded in cross-functional initiatives across People, Finance, GTM , Legal, Recruiting, and Technical Solutions — translating ambiguous business problems into scoped, buildable solutions and owning delivery end-to-end. This is not a generalist BSA role. Each Senior BSA will own a cluster of business functions end-to-end, acting as an internal product manager for their domain rather than processing inbound requests reactively. There are two openings, each covering a different domain: People, Recruiting, Legal or Finance, GTM, Procurement As the role evolves alongside AI, Senior BSAs leverage agentic tools for data aggregation and context gathering while remaining the critical human-in-the-loop layer — owning business context and product outlook, validating use cases, managing stakeholder relationships, and making the judgment calls agents can't. 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 You’ll Do: Discovery and scoping: Translate ambiguous asks from business stakeholders into well-defined requirements that Business Systems Engineers can build against. Many stakeholders don't know what they want or the cross-functional impact of what they're asking for — you surface both before engineering begins. Cross-functional visibility: Identify dependencies, downstream impacts, and integration considerations that requesting teams miss. Proactive opportunity identification: Develop deep domain knowledge to identify automation and AI opportunities before they become inbound requests, shifting the team from reactive in