Ai Deployment Manager Jobs

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. Fin is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Fin Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent. Founded in 2011 and trusted by over 30,000 global businesses, Fin is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers. What’s the opportunity? We’re hiring an Engineering Manager for our AI Models Infrastructure Team in the AI Group . The AI Models Infrastructure team builds and operates the foundational infrastructure th

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? We’re looking for Senior Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack. Our group is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated Engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and me

We’re looking for a Staff Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you’ll set technical direction and build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents. This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. Set technical direction for the team, balancing experimentation with reliability, maintainability, and long-term platform thinking. Partner cross-functionally with teams across the engineering organization to understand engineering needs, identify workflow friction, and scale high-impact solutions

This role will join Datadog’s Data Visualization organization, a team responsible for the visualization experiences that power dashboards, notebooks, investigations, and product workflows used across the platform. The team is a highly product-oriented organization, building AI-native experiences that help customers understand, investigate, and interact with complex operational data. As a Staff Software Engineer, you will provide technical leadership in applying AI technologies to customer-facing product experiences, helping shape how users interact with Datadog through agents, conversational interfaces, and intelligent investigation workflows. You will partner across engineering and product teams to develop reliable, scalable, and trustworthy AI-powered experiences while helping establish AI engineering expertise within the broader organization. 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 design and delivery of AI-powered product experiences across Datadog’s visualization and investigation surfaces. Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes. Drive innovation in context engineering, prompt engineering, evaluation frameworks, and AI application reliability. Partner with product and engineering teams to improve investigation workflows and help customers discover insights more efficiently. Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments. Provide technical leadership and mentorship while helping establish AI engineering best practices across the Data Visualization organization and broader Graphing group. Who You Are: You have extensive softw

We’re looking for an experienced sourcing leader to join the Datadog Procurement team and help grow the Strategic Sourcing group. Make an impact by partnering closely with senior technology and business leaders, owning our fastest-growing AI, neocloud, and inference spend end-to-end, and continuing to prove the value that Strategic Sourcing brings to the organization. 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 AI spend category end-to-end, covering foundation-model and AI APIs, AI development and productivity tools, and AI-enabled SaaS (with neocloud and inference compute as an emerging area), while developing and executing category strategies aligned to business objectives Champion AI and automation adoption across the sourcing function by identifying tools (e.g. Claude, ChatGPT) and building repeatable workflows that make sourcing faster, smarter, and more scalable Lead high-value AI vendor negotiations spanning foundation-model and API agreements, AI development and productivity tools, and AI SaaS, structuring seat- and consumption-based pricing across net-new purchases and strategic renewals, and building neocloud and GPU-capacity capability as the category grows Partner with Engineering and Finance to turn architectural and consumption trade-offs into commercial business cases, forecasts, and savings targets Build pricing and consumption models and apply FinOps discipline to quantify buying scenarios and uncover savings across a fast-moving spend base Work alongside executive and senior technology leadership as a trusted advisor on AI and neocloud investment decisions, influencing strategy and commercial trade-offs at the leadership level Track category KPIs (savings, pipeline, cycle time), monitor AI market, vendor, and pricing trends,

Datadog’s Product Analytics suite spans Product Analytics, Session Replay, Feature Flags, and Experimentation. Together they give product teams a complete, quantitative and qualitative picture of how users experience their applications, plus the tools to release, measure, and improve those experiences with confidence. Our team of Applied Scientists makes this space smarter and more autonomous, researching, prototyping, and industrializing AI/ML capabilities that make the suite proactive and agentic by default: AI-driven event understanding and instrumentation, conversational analytics, automated insight reporting, and UI/UX issue detection from session replays. The ambition is to let product teams act with autonomy, moving from question to insight to safely released change without depending on engineering or analysts. As the Engineering Manager for this team, you’ll lead a team of Applied Scientists through an early-stage, high-impact opportunity: defining the team’s technical vision, growing its footprint, and shaping how AI capabilities get built and delivered across the suite. This is greenfield work, both in the R&D itself and in the team you’ll grow around it. 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 and grow a team of Applied Scientists researching, prototyping, and industrializing AI/ML capabilities across the suite Define the technical vision and roadmap for the suite’s agentic and proactive AI/ML capabilities: event understanding, conversational analytics, insight reporting, and session-replay issue detection Stay hands-on as a technical contributor and reviewer, helping the team move from research prototypes to production-grade capabilities Shape how AI capabilities get built and delivered across the suite, partnering closely wi

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

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

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

AI agents are transforming the way developers interact with software - and databases are no exception. We're seeking a Senior Software Engineer to join our AI Interfaces team within AI Builder Experience (ABX), where you'll provide technical direction, shape architecture, and build the core products that make it seamless for developers and AI agents to work with MongoDB. Our team owns the surfaces through which humans and agents connect to MongoDB - including the MongoDB MCP Server, Agent Skills, our Intelligent Assistant Platform, and purpose-built agents. In short: if it's how an agent talks to MongoDB, we're building it. This is a new team charting new territory, and as a Senior Software Engineer here, you'll be right at the frontier - building the technologies that let AI applications and agentic workflows work seamlessly with MongoDB at scale. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects end to end with minimal guidance. We're looking for product-minded engineers who thrive on autonomy and take pride in shipping. MongoDB engineering teams pride themselves on building high-quality software and living our cultural values every day - we value intellectual curiosity and honesty, and building together in an environment that prioritizes collaboration over competition. This position requires participation in a 24/7 on-call rotation to ensure business continuity and incident response capabilities. This role can be based out of our Gurugram office. Position Expectations Work closely with research, product management, product engineering, product design, peers, as well as other teams within the company to define the first version and future evolution of our AI interfaces Design, build, and deliver well-tested core pieces of the platform - including the MongoDB MCP Server, Agent Skills, the Intelligent Assistant Platform, and purpose-built agents - in collaboration with othe

AI frameworks like LangChain, LlamaIndex, and n8n are quickly becoming the default way developers build with AI — and MongoDB wants to be the data platform that shows up everywhere they build. As part of the AI Builders Experience (ABX) org, we're standing up a brand new engineering team in Gurugram to make that happen, and we're looking for Senior Software Engineers to be among its founding members. The team owns the connective layer between MongoDB and third-party AI frameworks, platforms, and tools — the integrations that let developers use MongoDB effectively with the AI stack they've already chosen. That means shipping into some of the fastest-moving open-source ecosystems in tech, working mostly in Python and TypeScript, and partnering with the Database Experience (DBX) org when an integration needs new driver, platform, or product capability underneath it. This is a self-sufficient team by design. You and your engineering manager will be based in Gurugram, and the group is set up to own its area end to end: to decide how integrations get built, tested, released, and maintained, without waiting on another time zone to unblock the day-to-day. You'll work closest with the engineers sitting next to you, pairing on hard problems, reviewing each other's code, and dividing up a broad portfolio, while collaborating with product, partners, field teams, and open source maintainers as the work requires. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects with minimal guidance. Priorities can shift week to week based on framework changes, customer demand, and partner needs, so we're looking for product-minded engineers who thrive on autonomy and take pride in shipping. Much of your work will happen in public: sending pull requests to upstream repositories, working through external maintainer review cycles, and representing MongoDB in developer communities. MongoDB engineering team

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We’re looking for applied scientists with a Machine Learning and Artificial Intelligence background to build AI technologies and make Figma products more magical.. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build AI/ML models and systems to improve Figma’s products. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: You will be driving fundamental and applied research in AI. You will explore the boundaries of what is possible with the current technology set to build best in class models for Figma’s domains You will be combining industry best practices and a first-principles approach to build cutting edge Generative AI models, using techniques like Supervised Finetuning (SFT), Reinforcement Learning (RL), prompt improvements and synthetic data generation Work in concert with product and infrastructure engineers to improve Figma’s products through AI powered features Collaborate closely with product managers and engineers to transform user feedback into requirements for AI systems Build evaluation systems to measure and improve quality of AI features in Figma products We'd love to hear from you if you have: Extensive experience in building generative AI features through prompt engineering, and fine tuning models in production environments Experience working on deep learning and generative AI frameworks li

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart's Enterprise Solutions team is building a first-of-its-kind business: embedding directly with enterprise retail and CPG partners to design, sell, and deliver AI-powered solutions at scale. We are a small, senior, field-first pod—part startup, part consultancy—defining the playbook as we go. As the AI Solutions Architect, you own the data and AI architecture, integration design, and governance across every engagement the pod runs. You are the person who makes Instacart's Intelligence Platform actually work inside real partner environments. This is a hands-on, field-first role—you will embed with partner engineering teams to map data ontologies, design integrations, and co-build solutions that work in the real world, not just on a whiteboard. About the Job Own data modeling, integration design, and governance across every engagement; serve as the s

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Why this role is on the menu The Legal department at Instacart is scaling rapidly across new business models, ad formats, and retail partnerships, and the systems and workflows that support it need to keep pace. Right now, legal operations, technology, and AI enablement are evolving in parallel without a single leader owning the strategy end-to-end. This role exists to close that gap: to build the infrastructure, tooling, and team capabilities that make the legal function faster, smarter, and more accountable. Twelve months from now, Instacart will have a modern contract lifecycle management system, a deployed AI enablement program with meaningful adoption, and a legal operations team with clear KPIs and the processes to sustain them. If you thrive at the intersection of law, operations, and technology, and want to build something that lasts, this role is for you &