Generative Ai Engineer Jobs

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

About the Role OKX is looking for a Senior Director of AI to lead both people and product — building and managing a high-calibre AI team while staying deeply involved in the design, evaluation, and production deployment of autonomous agent systems. This role calls for a leader who leads by doing: technically grounded, sharp on product judgment, and able to translate both into tangible business outcomes. What You'll Do Team Leadership — Build, manage, and develop a team of AI engineers and researchers; own hiring, growth, and performance across the function Agent Product Delivery — Lead end-to-end delivery of autonomous AI Agent products, covering the full lifecycle from requirements and architecture through to production operations Eval-Driven Development — Establish benchmark-driven evaluation frameworks that replace manual iteration with quantifiable quality signals across agent systems Agent Harness Design — Design and implement end-to-end Agent Harness infrastructure to ensure agent stability and reliability in complex, real-world scenarios LLM Orchestration — Orchestrate creative reasoning steps alongside deterministic guardrails, finding the right balance between flexibility and control Engineering Workflow Integration — Embed AI Agent capabilities deeply into core products and engineering pipelines, improving both developer productivity and business value Cross-functional Alignment — Collaborate with product, engineering, and business teams to ensure technical direction stays tightly aligned with strategic priorities What We're Looking For Must-have Master's or PhD in Computer Science, Artificial Intelligence, or a related field (PhD preferred) 10+ years of experience in AI/ML research, productization, or platform development, including core technical or leadership roles at globally recognized technology companies Deep expertise in LLMs and Generative AI, deep learning, reinforcement learning, recommendation systems, and related areas Proven track record of t

This is Adyen Adyen provides payments, data, and financial products in a single solution for global customers like Meta, Uber, H&M, and Microsoft, making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. We create an environment with opportunities for our people to succeed, backed by a culture that encourages ownership and provides the support to truly own your career. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team, delivering innovative and ethical solutions that help businesses achieve their ambitions faster. The Opportunity Adyen is building a top-tier AI engineering team in San Francisco to drive our next chapter of innovation using AI globally across the entire company. This is a highly technical, hands-on role focused on the exploration and application of cutting-edge AI research within the financial technology sector. As a Member of Technical Staff , you will operate with a high degree of autonomy and responsibility , delivering strategic, high-impact outcomes that bridge the gap between advanced AI research and production-grade applications at a global scale, potentially impacting trillions of dollars in transactions annually. What You'll Do: Innovate and Deploy: Drive the execution of Adyen's AI strategy , focusing on the practical application of Generative AI (GenAI) and other AI methodologies in finance . This includes contributing to Adyen's efforts in key research areas such as AI agents for data analysis and operational workflows , human-in-the-loop for integrity risk , and development of foundation models . For instance, you might contribute to initiatives like the Data Agent Benchmark for Multi-step Reasoning (DABStep) , which evaluates AI agents on real-world data analysis tasks, including those from the financial sector. Build Production-grade Applications: Bridge the gap between cutting-edge AI research and production by imp

Opportunity Overview: As a Lead Applied Scientist, you’ll join our growing team of world-class applied scientists and clinical experts to deploy machine learning models that help automate burdensome administrative clinical practices. Our AS team’s work is focused on designing, prototyping, and partnering with AI Engineering to deploy and monitor production models which extract or predict relevant clinical findings from structured and unstructured data sources. What you’ll do: Design and develop advanced machine learning algorithms for retrieval, classification and generative use cases. Write and maintain reusable codebases to perform data preprocessing, model training, and model evaluation Provide scientific and machine learning best practice guidance to junior engineers Work cross-functionally with diverse stakeholders, including product managers, clinicians, and technical leadership to align ML solutions with Cohere’s core objectives. What you’ll need: Must-haves Minimum 7+ years of experience in applied ML with a masters degree or 5+ years with a PhD, ideally in a senior or lead role in a large technology or healthcare company Clear understanding of model building, model maintenance and the measures that optimize models for production use Understand experimental design and can independently perform collection, measurement, and interpretation of results Expert in Python with experience in deep learning frameworks (e.g., PyTorch) Hands on experience building deep learning models (e.g., transformers) for NLP tasks MS or PhD required Nice-to-haves Experience with generative AI or Retrieval Augmented Generation (RAG) Experience working with unstructured healthcare data (e.g., clinical notes) Experience with OCR or image-based document understanding techniques Hands on experience using AWS tools such as SageMaker Studio ISMS roles and responsibilities Good knowledge of Information practices. Assist the manager in all the information security activitie

CAPCO POLAND We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on innovative AI and automation initiatives for leading financial institutions. At Capco Poland, we're not just another consultancy – we're the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we help clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management. ENGAGEMENT OVERVIEW We are seeking an experienced AI Agent Engineer (Power Platform & Copilot Studio) to join our growing team and support the development of AI-driven automation solutions across enterprise business processes. This role requires strong hands-on experience with Microsoft Power Platform , particularly Copilot Studio , alongside a solid understanding of Generative AI concepts and conversational AI development. The scope of services includes designing, developing, and deploying intelligent AI agents that improve operational efficiency, enhance user experiences, and drive business value. Collaborating with business stakeholders, product owners, and technology teams, you will deliver scalable, secure, and high-quality AI solutions aligned with governance standards and best practices. KEY RESPONSIBILITIES AI Agent Development Design, develop, and deploy AI agents and automation solutions to support business process optimization. Build and maintain conversational AI solutions using Microsoft Copilot Studio and the wider Power Platform ecosystem. Design effective conversational flows and user experiences. Integrate AI solutions with enterprise applications, APIs, and business processes. Implement monitoring, analytics, and continuous improvements to enhance solution performance and adoption. Solution Delivery Collaborate with business and technology stakeholders to gather requirements and define solution designs. Translate business needs into scalable

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Location Singapore Department NAND Device Engineering Project Title AI-Enabled Device Characterization Automation and Intelligent Engineering Workflow Platform Project Description As an AI / Data Science Intern in the NAND Device Engineering organization, you will participate in the development of AI-Enabled solutions that enhance engineering productivity, accelerate device characterization, and improve data-driven decision-making for advanced 3D NAND technologies. This internship provides an opportunity to apply Artificial Intelligence, machine learning, data science, and automation techniques to complex semiconductor engineering datasets. The project focuses on developing intelligent automation workflows, AI-assisted analysis platforms, and Agentic AI solutions that streamline device characterization activities, automate engineering insights generation, and improve project execution efficiency. Working alongside experienced engineers, you will gain exposure to semiconductor device development, large-scale data analytics, and emerging Generative AI technologies within a manufacturing and product development environment. Objective of the Project Develop an AI-Enabled platform that automate

About the team The AI Deployment Engineering team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We serve as trusted technical advisors, helping customers and partners move from early experimentation to production-scale AI systems. As a Partner AI Deployment Engineer focused on AWS, you will operate at the center of one of our most strategic partnerships, driving joint customer success and enabling AWS and partner ecosystems to scale adoption of OpenAI-powered solutions. About the role We are looking for a highly experienced technical leader to serve as the primary technical counterpart to AWS field leadership (Solutions Architects, Specialists, and Partner teams). This role goes beyond individual deal support—you will shape strategy, define engagement models, and build repeatable systems that scale across AWS globally. You will work across pre- and post-sales, guiding complex enterprise customers from ideation to production while enabling AWS and partners to independently drive deployments. You will combine deep technical expertise, strong judgment, and ecosystem leadership to maximize impact across a portfolio of high-priority opportunities. This role can be based in either Bangalore, Mumbai or Delhi . In this role, you will: Strategic AWS Engagement & Influence Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams. Influence joint account strategy and technical direction for high-priority opportunities. Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices. Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem. Complex Deal Leadership & Execution Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements. Guide customers from early ideation through architecture design, prototyping, and production depl

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are seeking a technically proficient, business-minded AI Deployment Engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Solutions Architecture Lead. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research

About the team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. As an AI Deployment Engineer (ADE) in the OpenAI for Government team, you’ll help government agencies transform their organization through solutions such as automated content generation, contextual search, and novel applications that make use of our newest, most exciting models and technology. About the Role We are looking for a driven solutions leader with a product mindset to partner with our public sector customers and ensure they achieve tangible value with GenAI. You will pair with government agencies (federal, state, and local), policymakers, and other public institutions to establish a GenAI strategy and identify the highest value applications. You’ll then partner with their technical teams, subject matter experts, systems integrators, and implementation partners to move from prototype through production. You’ll take a holistic view of their needs and design an architecture using the OpenAI API and other services to maximize customer value. You will collaborate closely with Sales, Solutions Engineering, Global Affairs, Applied Research, and Product teams. This role is based in Washington, DC. We offer relocation support to new employees. In this role, you will: Deeply embed with our most sophisticated public sector customers as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API and other OpenAI products. Work with senior customer stakeholders to identify the best applications of AI in their industry and to build/qualify a comprehensive backlog to support their AI roadmap. Intervene directly to accelerate customer time to value through building hands-on pr

About the team The AI Deployment Engineering (ADE) team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We act as trusted advisors and technical partners to our customers, helping them build and execute their AI adoption strategy post-sale. Our mission is to develop a strong backlog of GenAI use cases tailored to each customer’s industry and to drive these initiatives from prototype to production through hands-on technical guidance and partnership. As a Partner ADE, you’ll support systems integrators and their most strategic customers transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the role We are looking for a driven solutions leader with a product mindset as the founding Partner ADE to own the technical engagement with our systems integrators (including GSIs, RSIs, and boutique SIs) and ensure their customers achieve tangible business value with GenAI. You will help partners identify high-value use cases and provide technical enablement through the implementation of AI solutions. Your efforts will accelerate partners’ time to unlock distribution and adoption, ensuring they deliver exceptional results for our joint customers while maintaining high-quality standards. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Head of Solutions Architecture. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Deeply embed with GSIs, RSIs, and boutique SIs as the technical lead, serving as their technical thought partner to ideate and build novel applications on our API for their customers. Work with senior SI and customer stakeholders to identify the best applications of GenAI in their industry a

As an AI Security Engineer , you will work at the intersection of software engineering, cybersecurity, and artificial intelligence. You will design and build security tools, assess AI-powered applications for vulnerabilities, evaluate third-party and open-source AI technologies, and help establish secure development standards for AI systems. This is a hands-on engineering role for someone who enjoys building solutions, solving complex technical problems, and exploring emerging security risks across technologies such as Generative AI, RAG, and agentic systems. What You'll Do Design, build, and implement tools for AI security testing, penetration testing, red teaming, and continuous vulnerability assessment. Develop mock and test AI applications to evaluate internal and third-party AI security solutions. Identify and assess security risks within AI-enabled applications and workflows. Develop security requirements, standards, and best practices for securely building and deploying AI applications. Evaluate third-party vendors, open-source tools, libraries, and AI technologies from a security perspective. Integrate security testing and evaluation capabilities into CI/CD pipelines and development workflows. Build scalable security tooling and automation that can be adopted across different teams and environments. Troubleshoot applications and solve complex engineering and security problems. Partner with engineering teams, security professionals, customers, vendors, and business stakeholders to understand requirements and deliver practical solutions. Create clear technical documentation covering tools, features, security assessments, testing methodologies, and findings. What You'll Bring 5+ years of software development experience building and supporting production applications. Strong hands-on programming experience with Python. Experience working with RESTful APIs and structured data formats such as JSON, XML, CSV, and HTML. Experience with CI/CD pipelines and mod

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Position Overview The AI Platform Engineer builds and operates the machine learning and generative AI platform used by teams across Abbott Cancer Diagnostics. You'll own the full model lifecycle in production — data and feature pipelines, training and experimentation, evaluation and promotion, serving, and monitoring — along with the platform services, compute and tooling underneath it. This is hands-on infrastructure work backed by solid platform engineering practice: making inference fast and cheap, making the path from experiment to production repeatable and auditable, and shipping interfaces other engineers can build on — in support of software that ultimately reaches patients. Essential Duties Include, but are not limited to, the following: Build and maintain data, feature, and training pipelines for ML and LLM workloads — ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model. Implement automated evaluation and promotion gates — performance benchmarks, regression checks, and validation criteria that determine whether a model advances toward production. Automate the model lifecycle end to end through CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback. Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling,