Senior Applied Ai Partner Solution Engineer Jobs

About the role Scale's Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. As a Staff Applied AI Engineer, you'll raise the bar for how AI gets built, governed, and evaluated across the team. You'll define standards that other engineers adopt, such as evaluation methodologies for agents and MLOps practices, while acting as the senior technical voice for the most sensitive AI decisions our clients face. What you'll do Define standards for responsible AI, model governance, and production MLOps that get adopted broadly across the Global Public Sector team Build or validate the highest-risk parts of strategic AI systems and use those systems to establish standards other teams can adopt. Architect AI systems designed to prevent systemic failure, and lead the resolution of the most severe incidents tied to model safety or data integrity Build reusable AI capabilities, such as production-ready agent implementations built on proven architectures, fine-tuned models, or evaluation methodologies, that other engineers and clients can build on Advise on which new AI developments are worth adopting, and help set the technical roadmap for the domain Act as the senior technical partner to client leadership on AI strategy Coach Senior Applied AI Engineers, delegate ownership of technical domains, and build systems and practices that enable multiple teams to deliver safer AI Contribute to recruiting and representing Scale's AI work externally What we look for 7+ years of engineering experience, with a multi-year track record owning AI/ML systems in production Experience judging the quality of training data, selecting the right adaptation method for a given model, evaluating fine-tuning results, and balancing serving cost, latency, and quality trade-offs Experience owning an AI-powered product end to end, including direct involvement in the AI's behaviour rather than implementing ML work scoped by another team A tr

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

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. At Snowflake, we are building a high-impact team to help the world's most innovative companies unlock the power of AI. As a Senior Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself. You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures

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 ship AI products. THE ROLE We’re hiring a People Business Partner to support our team during a critical phase of growth. This is a highly strategic, high-impact role for someone who has partnered closely with leadership teams and helped organizations scale with intention. You will be deeply embedded with managers, bringing clarity and rigor to how teams are structured, how leaders operate, and how talent is developed across the organization. You’ll help shape team effectiveness, identify critical talent gaps, drive talent and performance strategies that enable high-performing teams, and build the people practices and change management approaches that allow us to scale with both speed and discipline. This role requires strong business judgment and the ability to operate with deep context. You’ll partner closely with leaders to navigate complex organizational decisions, anticipate challenges before they surface, and bring a clear point of view on what great looks like at every level of the organization. RESPONSIBILITIES Strategic partnership to leadership Serve as the trusted people partner to leadership, maintaining deep business context and translating it into people priorities by proactively surfacing systemic issues, risks, and opportunities before they become urgent. Bring data-driven insights to advise management on org design, succession planning, performance, retention, and engagement. Build management capacity across the org, equip

Overview: Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale — combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets. You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership. This role is hybrid in our Toronto Office What You'll Do: Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure. LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code — not just prompts. Multi-channel session management: stateful user interactions that move seamlessly across channels. Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back. Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes. Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads. Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors. Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them. Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable. Partner with product and compliance stakeholders to encode domain rules into the system. Set engineering patterns for a growing team: code review, observability, incident habits. What You Have: 6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestratio

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. As a Staff Forward Deployed Engineer, Applied AI on our Cortex AI team, you will be a hands-on technical leader and trusted partner to our most strategic customers. You will own the end-to-end delivery of enterprise AI programs, leading a team of 2–4 engineers while staying deeply technical yourself . You will set the technical direction for your customer engagements, mentor your team, and serve as the senior technical voice at the intersection of product, engineering, and customer success. Note: This is a customer facing role & require frequent travelling within USA mostly IN THIS ROLE AT SNOWFLAKE, YOU WILL: Lead Customer Programs : Own the full lifecycle of complex, multi-engineer AI engagements – from scoping and architecture through deployment, monitoring, and handoff. Be accountable for delivery quality and customer outcomes for the projects you lead. Own AI Quality : Define what "good" means for each engagement. Translate ambiguous customer goals into measurable quality metrics, evaluation frameworks, and golden datasets – then run systematic eval loops to hill-climb on agent quality, catch regressions before customers do, and continuously raise the bar on accuracy, faithfulness, and safety. Set the standard for how the team measures and improves AI systems in pr

About the Role Together AI is building the AI Native Cloud — an end-to-end platform for generative AI lifecycle, integrating fast, reliable inference, and model-shaping services with cutting-edge AI cloud infrastructure. We are looking for a seasoned Senior Technical Recruiter to partner closely with AI Research and Engineering leadership to scale world-class research teams across kernels, inference optimization, applied AI and model shaping. This role is ideal for someone who understands the unique dynamics of recruiting top-tier AI researchers and research engineers in a highly competitive market and can operate as a strategic talent partner to technical leadership. Responsibilities Partner with executives, research leadership, and hiring managers to define and execute hiring strategies Lead full-cycle recruiting for specialized AI talent, including researchers, research engineers, applied scientists, and ML systems engineers Build and nurture relationships with top AI talent across academia, open-source communities, research labs, and industry networks Drive exceptional candidate experiences from initial engagement through offer close, with a strong focus on relationship building and long-term talent cultivation Provide market intelligence on AI talent trends, compensation, competitive hiring landscapes, and emerging research organizations to influence hiring strategy and organizational planning Collaborate cross-functionally with sourcing, coordination, people operations, and leadership teams to continuously improve recruiting processes and operational excellence Design and refine interview processes tailored for research hiring, including technical evaluations, publication reviews, and research presentation loops Requirements 5+ years of technical recruiting experience at high-growth technology companies, with a proven track record hiring exceptional AI researchers, research engineers, applied scientists, or ML infrastructure talent at leading AI labs, hyper-sc

CSQ426R319 Senior Customer Enablement AI Programs Manager As a Senior Customer Enablement AI Programs Manager, you will own the AI strategy and roadmap for the Scaled Customer Enablement Agent Suite — bringing together GTM activation, applied AI, and enablement strategy. You will define how the agents retrieve, reason over, and surface enablement insights to global Account Teams, turning learner and account data into prescriptive, just-in-time recommendations that improve account health and grow the number of trained users across our customer base. By automating GTM processes, you will ensure Account Teams and customers receive consistent Databricks enablement planning resources. You will be responsible for driving the AI roadmap for customer enablement, compounding enablement as a strategic leverage for our customers and for Databricks. This role will report to the Global Customer Enablement Practice Senior Director. This is an exciting opportunity for a motivated and innovative entrepreneur with a passion for working across departments and across regions. The impact you will have: Own the product roadmap and architecture direction for the Scaled Customer Enablement Agent Suite — defining the data inputs, retrieval sources, and agent behaviors that generate enablement recommendations. Lead the rollout and drive field adoption of the Scaled Customer Enablement Agent Suite, delivering automated learning insights and proposals to Account Teams. Structure the enablement knowledge base for retrieval — designing content schemas, metadata, and chunking so agents return accurate, grounded outputs — and maintain the underlying customer enablement playbook. Define the signals and triggers — usage patterns, learning milestones, and account-health thresholds — that prompt the agents to surface a free-to-paid enablement opportunity to Account Teams at the right moment. Partner with technical teams to embed enablement calls-to-action and insights di

About the Role OpenAI’s largest and most strategic customers are turning AI ambition into deployments that change how their organizations work. As a Delivery Lead, you will own delivery of priority AI initiatives for these customers, leading complex, high-impact deployments from planning through launch and adoption. You’ll establish an integrated delivery plan, drive execution against launch commitments, resolve blockers, and lead progress toward measurable customer value. You’ll partner closely with account and technical teams, FDEs, customers, and delivery partners to turn customer priorities into successful deployments. You’ll bring a clear view of delivery progress, risks, and expected outcomes, helping teams make informed decisions and connecting successful execution to consumption and growth. This is a senior, customer-facing role for someone who can move between executive conversations and practical details that determine whether a deployment succeeds. You bring technical fluency, sound judgment, and the ability to create clarity and drive action in complex, evolving environments. What You’ll Do Own delivery of priority AI initiatives. Lead complex customer engagements from scoping and planning through deployment, launch, and initial adoption. Build and drive an integrated delivery plan. Establish clear scope, milestones, accountable owners, dependencies, resource needs, and success measures across customer, OpenAI, and partner teams. Resolve blockers and drive decisions. Identify risks early, work through dependencies and resource constraints, and bring the right stakeholders together to resolve tradeoffs and keep delivery moving. Lead launch readiness and activation. Drive rollout and enablement planning, address technical and organizational readiness gaps, and remove barriers to initial adoption and usage. Connect delivery to customer value. Define expected outcomes and measurement approaches with customers and account teams. Track adoption and consumption

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on our Enterprise team, your role is to guide some of the UK's largest businesses to the frontier of AI and help them deploy Claude into their operations, their products, and their ways of working. You will become the go-to Claude Platform specialist and trusted technical advisor for your customers, advising their engineering teams on architecture, agent design, and evaluation, and working with the C-level and senior executives who sponsor these programmes to show the business value Claude can create and help them reach a confident decision to build on Claude. Enterprise deals are different. Procurement cycles are longer, more stakeholders are involved, and success depends on being able to connect the technical work to the outcomes the boardroom cares about. You will be as comfortable advising an engineering team on evaluation and architecture as you are presenting a value case to a CIO or CTO, and you will carry the technical thread across every stage of a multi-quarter engagement. You will partner closely with Enterprise Account Executives and Applied AI Architects to take each customer from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude. Once they have decided, you set their systems integration partner up to deliver, agreeing the target architecture and what good looks like, and you stay close as the customer's technical advisor on Claude throughout deployment, while the partner does the build. Working alongside Anthropic's Product and Engineering teams, you will use your knowledge of the Claude Platform to advise on evalu

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on our Enterprise team, your role is to guide some of Germany's largest businesses to the frontier of AI and help them deploy Claude into their operations, their products, and their ways of working. You will become the go-to Claude Platform specialist and trusted technical advisor for your customers, advising their engineering teams on architecture, agent design, and evaluation, and working with the C-level and senior executives who sponsor these programmes to show the business value Claude can create and help them reach a confident decision to build on Claude. Enterprise deals are different. Procurement cycles are longer, more stakeholders are involved, and success depends on being able to connect the technical work to the outcomes the boardroom cares about. You will be as comfortable advising an engineering team on evaluation and architecture as you are presenting a value case to a CIO or CTO, and you will carry the technical thread across every stage of a multi-quarter engagement. Much of this work happens in German, with German executives and engineering teams, so native or fluent German is essential for the role. You will partner closely with Enterprise Account Executives and Applied AI Architects to take each customer from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude. Once they have decided, you set their systems integration partner up to deliver, agreeing the target architecture and what good looks like, and you stay close as the customer's technical advisor on Claude throughout deployment, while the partner does the

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the AI Platform team within the Platform group, you'll build and operate the LLM and agent infrastructure that every team at Coinbase depends on. This team owns the company's single path to large language models and the full agent lifecycle: build, deploy, run, observe, and improve. You'll lead multi-quarter technical initiatives across the platform, from gateway and runtime systems to knowledge bases and applied AI agents, directly shaping how Coinbase scales AI across the organization. What you'll do: Own the architecture and delivery of core platform systems including the LLM Gateway (60+ models, auth, PII redaction, fallbacks, cost optimization), AI Hub, and agent runtime with microVM sandboxes and governed MCP gateway Drive the design and implementation of Knowledge Base infrastructure, connecting data sources to auto-provisioned vector and markdown stores queryable by any agent Lead AI FinOps capabilities including spend attribution, governance, and cost optimization across all AI workloads company-wide Partner across engineering, security, legal, finance, product, and external partners at frontier labs and major cloud providers to ship high-impact platform capabilities Build evaluation and observability tooling including LLM-as-judge harnesses, full tracing, and feedback loops that let subject matter experts refine production a

Overview We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. What You’ll Do Lead AI Engineering Across GRC Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence) Partner with product, data, and platform teams to translate business problems into scalable AI systems Stay Hands-On Contribute to architecture, code reviews, and critical path implementation Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.) Set engineering standards for performance, reliability, and cost efficiency Build and Scale Teams Lead and mentor a high-performing team of AI/ML and software engineers Drive hiring, coaching, and career development Establish a culture of ownership, speed, and technical excellence Drive Execution Deliver production-grade systems—not experiments Balance speed with rigor (security, privacy, compliance) Operate across multiple concurrent initiatives with clear prioritization Communicate and Influence Act as a bridge between engineering and business stakeholders Clearly articulate trade-offs, risks, and outcomes to senior leadership Align cross-functional teams around shared goals and timelines What We’re Looking For Proven Builder 10+ years in software engineering, with recent hands-on coding experience Demonstrated track record of shipping production systems at scale Experience with modern