AI Agent Engineering Intern

At Sendbird, we merge omnichannel AI with world-class, validated communication APIs to empower businesses in creating AI agents that enable meaningful customer connections at scale.Sendbird offers solutions with enterprise-level stability, security, and compliance. Over 4,000 leading global apps, including DoorDash, Match Group, Noom, and Yahoo Sports, trust…

Join Our AI Transformation TeamOur dynamic AI Transformation Team is dedicated to tackling intricate engineering challenges through innovative machine learning techniques, transitioning these solutions into impactful real-world applications. We specialize in creating agent systems designed to automate problem-solving, constantly refining and enhancing our approaches.Our mission is to seamlessly connect research with practical application by constructing platforms that utilize agentic AI for tangible engineering solutions.Key ResponsibilitiesArchitect and develop the foundational infrastructure for our Agent System Framework.Implement essential components of the agent runtime, focusing on orchestration, context management, tool execution, and memory abstraction.Work alongside cross-functional teams to quickly prototype and scale new agent functionalities into production environments.Design and enhance developer-friendly interfaces including CLI tools and SDKs.Minimum QualificationsA Bachelor’s degree in Computer Science, a related technical discipline, or equivalent practical experienceProven experience in at least two of the following areas:Designing and managing distributed systems or extensive backend systems.Building and deploying machine learning/AI systems, particularly those based on LLMs, in a production setting.Developing agent systems, workflow engines, or orchestration frameworks.Backend development proficiency in Python, Go, or C++.Preferred QualificationsMaster’s or PhD degree in Engineering, Computer Science, or a related fieldDemonstrated success in designing and implementing agentic AI system frameworks in real-world or large-scale contexts.Hands-on experience in developing LLM-based applications (e.g., for tool utilization, planning, reasoning systems).Experience in creating developer tools, such as CLI or SDKs.Contact UsFor inquiries, reach out to us at: recruit@furiosa.ai

Join us at the forefront of agentic AI, where you'll be part of a team that builds intelligent systems capable of deep understanding. At Sendbird, we are not just developing prototypes; we are deploying AI solutions at scale that genuinely think and adapt.About SendbirdSendbird is committed to shaping the future of AI-driven customer interactions. With over a decade of experience in creating robust infrastructures for chat, voice, video, and messaging APIs, we've established ourselves as the leading CPaaS platform for in-app communications. Trusted by over 4,000 brands and facilitating 7 billion messages monthly, we connect 300 million active users.Our clients include industry leaders like DoorDash, Match Group, Noom, Yahoo Sports, and Rakuten. Our track record speaks for our expertise and excellence.Recognizing the transformative potential of AI in customer communication, we pivoted to an AI-first strategy in December 2024, launching our AI agent for enterprise customer experience by February 2025. Our rebranding to Delight.ai in November 2025 encapsulates our mission: to not just enhance efficiency, but to restore the essence of personalized service—creating delightful experiences for customers.About Delight.aiDelight.ai acts as the AI concierge for customer interactions, ensuring continuity and understanding across various channels. Unlike other AI agents, our solution retains memory, learns individual preferences, and maintains context—delivering a truly personalized experience.Why Join as a Senior Software Engineer, AI Agent?In an industry filled with superficial solutions, Sendbird's AI Agent platform stands out for its robustness, scalability, and genuine intelligence. This is not just maintenance work; you'll shape the core platform, designing orchestration, RAG pipelines, evaluation, and observability that will impact millions of customer interactions for years to come.

Job ResponsibilitiesStay abreast of cutting-edge AI research trends, including LLM, Agentic AI, Diffusion, and Inference acceleration, and explore integration opportunities with our proprietary NPU.Lead groundbreaking AI research aimed at publication in top-tier academic conferences.Forge research collaborations with prestigious global institutions and manage associated projects.

Key ResponsibilitiesManage and operate the testing infrastructure for our software and hardware solutions.Conduct operations and maintenance on bare-metal equipment utilized for evaluations.Support the evaluation infrastructure to ensure successful product validation.

Key ResponsibilitiesDevise and execute comprehensive verification strategies for block/IP/SoC, establishing test benches to facilitate effective verification at various levels.Create and implement functional testing protocols based on the established verification test plans.Lead the design verification process to successful completion, adhering to defined metrics for functional and code coverage.Analyze, troubleshoot, and rectify functional discrepancies in the design, working closely with the design team.Engage in collaboration with cross-disciplinary teams, including Design, Modeling, Emulation, and Silicon Validation, to ensure superior design quality.

Key ResponsibilitiesIntegrate and validate IP blocks within the System on Chip (SoC) architecture while assisting in the physical implementation process.Formulate specifications, architecture, and operational scenarios at the SoC level.Comprehend standard interface specifications (e.g., PCIe) and chip operational scenarios to effectively configure integrated IP blocks.Conduct performance analyses through chip-level simulations focusing on bus and memory bandwidth, alongside FPGA prototyping.

Key ResponsibilitiesDesign, develop, and sustain Linux PCIe device drivers and kernel modules to optimize system performance.Enhance PCIe subsystem functionality, focusing on DMA, IOMMU, interrupts, and BAR mapping.Create user-space libraries and APIs that facilitate high-speed data transfers.Collaborate with hardware and firmware teams to construct comprehensive PCIe I/O pipelines.Devise effective memory management techniques and implement zero-copy data transfer mechanisms.

About the RoleWe are seeking a dedicated Security Engineer to report directly to the CTO. This role is instrumental in establishing the company's security framework and implementing a Zero Trust architecture across our organization.You will be responsible for developing security policies, configuring systems, managing accounts, controlling access, ensuring cloud security, and conducting penetration testing.Key ResponsibilitiesEstablish and execute an enterprise security strategy and policies based on Zero Trust principles.Build and operate identity and access management systems (SSO, IAM, RBAC, etc.).Design and configure security architecture for SaaS and cloud infrastructure (AWS, GCP, etc.).Diagnose and enhance security vulnerabilities within internal systems and services.Collaborate with development and infrastructure teams to integrate security practices (code reviews, CI/CD security, etc.).Set up and manage incident response systems and monitoring environments.

Key ResponsibilitiesDesign and define architecture/microarchitecture specifications while taking full ownership of one or more chip modules, implementing them in RTL.Achieve convergence of functionality and Power, Performance, Area (PPA) within the design.Develop and refine designs in RTL (System Verilog or other HDLs), iterating to optimize power consumption, timing, and area efficiency.Construct straightforward test benches and troubleshoot intricate logic simulations.Minimum QualificationsA Master's degree in Electrical Engineering, Computer Science, or equivalent practical experience.A minimum of 2 years of relevant industry experience in chip design, particularly in RTL design (architecture and implementation), logic synthesis, verification, and timing closure.Proficient in implementing microprocessor simulators using C++ or other high-level programming languages.Experience in modeling the PPA of designs.Familiarity with scripting languages for automating simulation and analysis processes.Preferred QualificationsA Ph.D. in Electrical Engineering, Computer Science, or related field is advantageous.Experience in accelerator design is a plus.Knowledge of highly pipelined designs and multiple-clock-domain designs is preferred.Understanding of machine learning algorithms, compiler technologies, processor design, accelerators, and memory hierarchies.Familiarity with Chisel or RISC-V architectures is an advantage.Contact InformationFor inquiries, please reach out to: recruit@furiosa.ai

Key ResponsibilitiesDevelop and maintain test automation solutions to validate NPU hardware and associated software stacks.Enhance efficiency in large-scale evaluation tasks through the maintenance of automation scripts and frameworks.Design solutions for structuring, analyzing, and visualizing evaluation data.Support the operation of testing environments based on CI/CD methodologies.

Key ResponsibilitiesAssess the Power, Performance, and Area (PPA) metrics of our designs during the chip architecture planning phase.Conduct synthesis, perform logic equivalence checking, develop SDC and UPF, and execute static timing analysis.Collaborate effectively with design houses to ensure optimal project outcomes.

About the TeamThe AI Success Engineer team at OpenAI collaborates with some of the world's most forward-thinking organizations to convert cutting-edge artificial intelligence into significant business outcomes. We support customers from initial deployment to large-scale enterprise integration, encompassing technical integration, workflow transformation, and ongoing product delivery.Our clientele includes rapidly growing digital natives as well as leading global enterprises, government bodies, and educational institutions. Each engagement represents a chance to influence the way AI reshapes work, productivity, and innovation. This pivotal role is integral to that mission.About the RoleAs an AI Success Engineer, you will serve as the primary post-sales contact for a select group of OpenAI's most esteemed clients. Your mission is to enhance account health and adoption, ensure technical readiness, uncover new use cases, and deliver measurable value through OpenAI's platform.This role uniquely combines technical leadership, program management, customer advisory, and product influence. You'll collaborate closely with client teams, analyze workflows, lead configuration and enablement, oversee deployment strategies, and guide clients toward impactful use cases that highlight the full potential of our platform.You will engage with Sales, Solutions Architecture, Product, and Research teams to ensure a seamless and successful customer experience at every touchpoint. Success in this position means accelerating adoption, deepening customer engagement, paving the way for strategic use cases that reach production, and helping our clients showcase tangible business value.

Key ResponsibilitiesCraft and implement a robust end-to-end security architecture tailored for SoC-based products.Develop features for Secure Boot and Anti-rollback mechanisms.Manage Key Provisioning alongside Hardware Root of Trust.Oversee Secure Lifecycle State management (LCS) for firmware, keys, and devices.Design and integrate security modules to enhance firmware and system-level defenses.Conduct thorough vulnerability assessments, attack surface evaluations, and implement memory protection hardening strategies.Integrate, validate, and optimize hardware cryptographic engines including AES/GCM engines, TRNG, PKA, RSA, PQC, and hash accelerators.Establish secure firmware update and rollback protocols along with comprehensive product lifecycle controls.QualificationsDeep understanding of embedded security principles, including Secure Boot, key management, and cryptography.Demonstrated experience with TLS, X.509, ECC, AES, and various cryptographic or security libraries.Proficient in C/C++ or Rust for developing secure system software.Experience identifying and analyzing security vulnerabilities in SoC/FPGA-based systems.Practical experience with hardware cryptographic engines and security IP blocks (e.g., AES/GCM, SHA accelerators, TRNG/DRBG, PKA).Solid understanding of firmware and key lifecycle management.Preferred QualificationsFamiliarity with TPM, HSM, TrustZone, OP-TEE, or related hardware security architectures.Experience in implementing secure firmware signing, provisioning, and deployment pipelines.Background in validating cryptographic engines under standards such as FIPS 140-3, NIST CMVP.Security engineering experience specifically for AI accelerators, networking chips, or SoCs.Contribute to development practices aligned with standards such as FIPS, PSA Certified, CAVP, and CMVP.

Join our dynamic team at Toss as an AI Engineer in the AI Operation Center! You will be part of an innovative team dedicated to building a real-time voice conversation system that interacts with customers, moving beyond traditional text chatbots to actual phone calls. Our AI must navigate various conversational scenarios, including interruptions, context shifts, and silences, to maintain a natural dialogue.This position will expose you to cutting-edge technologies such as LLM, Multi-Agent systems, Automatic Prompt Optimization (APO), and LLM-as-Judge, applied in the challenging environment of customer interactions. You'll be part of a team that doesn’t just stop at reading research papers but actively creates solutions based on real call data.

About Our TeamJoin the innovative AI Deployment Engineering team at OpenAI, where we are committed to the safe and efficient deployment of cutting-edge Generative AI applications for developers and enterprises. As trusted advisors and thought leaders, we collaborate closely with customers to develop a robust backlog of GenAI use cases tailored to their industries, guiding them through to production with expert technical support. In your role as an AI Deployment Engineer, you will empower major corporations to revolutionize their operations through transformative solutions in customer service, automated content generation, and pioneering applications leveraging our state-of-the-art models.About the PositionWe seek a proactive solutions leader with a product-oriented mindset to partner with our clients, ensuring they derive genuine business value from Generative AI. You will collaborate with senior customer executives to craft a strategic GenAI vision and pinpoint the most impactful applications. Additionally, you will work hand-in-hand with their technical teams to transition from prototype to full-scale production. By adopting a comprehensive approach to their requirements, you will design an enterprise architecture utilizing ChatGPT, the OpenAI API, and other services to maximize value for our customers. This position requires close collaboration with Sales, Solutions Engineering, Applied Research, and Product teams, and reports directly to the Head of Technical Success in the APAC region.This role is based in Seoul, South Korea, with a hybrid work model of three days in the office each week. Relocation assistance is available for new hires.Key Responsibilities:Become deeply integrated with our key platform customers as their technical lead, providing guidance and support to develop innovative applications utilizing our API.Collaborate with senior stakeholders to identify optimal applications of GenAI within their sector and establish a thorough backlog to support their AI initiatives.Actively engage to expedite customer time-to-value by creating hands-on prototypes and delivering strategic insights.Build and nurture relationships with customer leadership and stakeholders to facilitate the successful implementation and scaling of their applications.Contribute to our open-source resources for developers and enterprises.Enhance the Solutions Architect function by sharing knowledge, documenting best practices, and publishing resources in our internal and external repositories.Assess, synthesize, and present high-impact strategies that align with customer goals.

The landscape of AI agents is rapidly evolving. While many companies are still determining their direction, we have a clear vision and are seeking a talented individual to help us realize it.About UsDelight.ai is dedicated to shaping the future of customer experience through AI. For over a decade, we have developed robust infrastructure for communication—covering chat, voice, video, and messaging APIs—establishing ourselves as the leading CPaaS platform for in-app communications. Trusted by over 4,000 brands, our platform processes an astonishing 7 billion messages each month, engaging 300 million active users.Our technology has powered customer interactions for industry giants such as DoorDash, Match Group, Noom, Yahoo Sports, and Rakuten. We excel in our field—truly excelling.Recognizing early on that AI would revolutionize business-customer communication, we understood that our decade of infrastructure would soon be commoditized. The real value would shift towards intelligence, enhancing customer experiences and driving outcomes.Faced with a choice to safeguard our existing achievements or evolve, we chose the path of transformation.In December 2024, we pivoted fully to an AI-first approach in customer experience. By February 2025, we had launched our enterprise AI agent, leveraging a decade’s worth of conversation data, now enhanced with advanced intelligence. In November 2025, we rebranded to Delight.ai.Our name encapsulates our mission. The true potential of AI lies not solely in efficiency or cost reduction, but in restoring to customers the invaluable feeling of being genuinely understood and valued. Not merely satisfied—delighted.Our ProductDelight.ai serves as the AI concierge for customer interactions. Unlike typical AI agents that forget users after a conversation ends, our solution builds lasting memory, learns preferences, and maintains context across all channels—whether it’s chat, SMS, email, voice, or WhatsApp—ensuring a seamless experience. Our goal is to create AI that makes customers feel acknowledged, appreciated, and remembered.Why We Need an Applied AI EngineerThe next evolution of AI extends beyond chatbots responding to FAQs. We are developing agents that can reason, retain information, and act proactively and accurately at scale. We need a skilled engineer to construct the underlying framework that will support this innovation.This role merges research with real-world application. You will harness the latest advancements in LLMs, RAG, and agentic systems to create features that enterprise clients rely on daily—not just prototypes, but fully deployed and scalable solutions. Additionally, you will be expected to leverage AI tools within your workflow, automating processes, connecting APIs, and utilizing agentic CLIs to enhance your output, achieving results that far exceed what any individual engineer could accomplish alone.

# Join Our Team- The AI Platform team is on a mission to create a platform that enables everyone to use AI technology quickly and reliably. We technically support the use of AI across Toss.- We are developing the necessary tools and platforms for new AI systems such as Retrieval-Augmented Generation, Agents, and Assistants to be rapidly experimented with and reliably operated.- The platform we create is not just a simple toolkit; it is designed with scalability in mind, allowing AI technology to be implemented by more teams effectively.- Addressing unresolved problems means that collaboratively defining and structuring technical directions is crucial.- **Want to learn more about Toss’s data organization?** [→ *Toss Data Division Wiki*](https://recruit-data-division.oopy.io/)# Responsibilities- Integrate LLM-based components such as Retrieval, Generation, and Vector Search into a platform that various teams can reuse.- Provide features that integrate both SaaS and self-hosted LLMs and ensure stable operations.- Design the foundation for creating and experimenting with Agent systems more easily, including prompts, tools, and context configurations.- After experiments, ensure stable operation in the service by systematizing and tooling the serving and operational flow of RAG and Agents.- Develop a foundation to quantitatively evaluate the performance and quality of Agents and provide it as a platform.- Design a common environment and experience to enable rapid experimentation and application of AI systems not only within the team but also across other teams.- Structure unformatted technical elements and create directions that can expand into broader problems.# We Are Looking For- Individuals with experience applying technologies such as LLM, RAG, and Agents to real-world problems.- Those who can technically define unstructured problems and systematically solve them.- Candidates who have collaborated with multiple teams to develop and operate technology as if it were a product.- Those who can quickly adapt to new technological trends and integrate them naturally within the team.- Individuals interested in simplifying complex AI systems into a consistent and straightforward user experience.# Preferred Qualifications- Experience designing RAG components such as Retrieval, Generation, and Vector Search independently and integrating them at the system level.- Experience selecting and operating various LLM serving structures (OpenAI API, HuggingFace, vLLM) tailored to service situations.- Experience structuring various purpose-driven Agents and applying them in service operations is highly welcomed.- Experience proactively designing experimental environments or tools based on the requirements of platform users (internal developers, model engineers, etc.).- Experience creating and operating common platforms or RAG-based systems that can be extended across multiple projects or domains is especially desirable.# Resume Tips- If your past projects had significant impacts on the organization, please detail them.- Rather than just listing languages, platforms, frameworks, or technologies used, provide context about the project's objectives, the methods you employed, and how you solved the problems.- Include experiences where you resolved critical issues during platform operations or optimized performance/resources.- If you have contributed to open source by fixing bugs or enhancing functionalities, please share those experiences.# The Journey to Join Toss- Application submission > Job interview > Cultural fit interview > Reference check > Compensation negotiation > Final acceptance- The job interview will feature in-depth technical interviews focused on ML system design.# A Message for Future Colleagues“We don’t just serve rapidly evolving AI models; we build systems that ensure these models operate stably and are continuously improved.”- The AI Platform team is responsible for the serving, experimenting, and operating infrastructure of various AI technologies such as LLM-based services, RAG systems, and search infrastructure to ensure smooth operation in production environments.- We efficiently manage GPU resources and clusters, utilizing vLLM, Triton, Model Registry, etc., to automate experiments and deployments.

About AnthropicAt Anthropic, we strive to develop AI systems that are not only reliable and interpretable but also steerable, ensuring they are safe and beneficial for both our users and society. Our rapidly expanding team consists of dedicated researchers, engineers, policy experts, and business leaders who collaborate to create transformative AI solutions.Your Role as a Product Engineer in Applied AIAs a technical Product Engineer on the Applied AI team, you will serve as a trusted advisor to clients implementing Claude. Your collaboration with customer product and engineering teams will be crucial as they develop and launch innovative products powered by Claude. You will offer guidance on architectural design, create evaluation frameworks, and facilitate the adoption of the latest implementation techniques for large language models (LLMs).Collaboration and SupportWorking in tandem with our Sales, Product, and Engineering teams, you will lead customers through technical discovery and ensure successful deployment. Your blend of engineering acumen and interpersonal skills will empower clients to unlock the potential of LLMs and devise solutions to complex business problems while upholding our commitment to safety and reliability.Key Responsibilities:Act as a technical consultant for Anthropic customers deploying new products and workflows using our models, overseeing their journey from initial discovery to deployment while coordinating across various internal teams to ensure customer success.Collaborate with account executives to gain a thorough understanding of customer product needs and design technical solutions that align with business goals.Provide guidance on architectural decisions, assisting customers in building cutting-edge products and workflows using LLMs through our API.Create tailored pilots, prototypes, and evaluation tools that demonstrate the advantages of integrating our models into customer workflows via our API.Conduct hands-on technical workshops and code reviews with customer engineering teams.Identify prevalent design patterns and share insights with our Product and Engineering teams.Maintain up-to-date knowledge of advancements in LLM capabilities, implementation strategies, and AI product development tools.Occasionally travel to client sites for workshops, implementation assistance, and relationship building.Participate in conferences, deliver presentations, and author blog posts and white papers on relevant AI topics.

Role overview The Compiler team at FuriosaAI builds the software stack that enables machine learning models to run efficiently on the company’s AI accelerator hardware. This Software Engineer - Compiler (AX Engineer) role is a new position based at the Seoul headquarters. The focus is on developing and refining AI-assisted engineering workflows, identifying bottlenecks, running experiments, and building tools and guides that the team can use repeatedly. While the role is part of the Compiler team, deep compiler expertise is not required. Daily work includes code reviews, debugging, CI and testing, documentation, and project management. This position is a good fit for someone who enjoys shaping new roles and working through open-ended challenges. What you will do Identify challenges and opportunities in engineering workflows, including development, code review, debugging, CI/testing, documentation, and project delivery. Research, prototype, and benchmark AI and automation tools, such as coding agents, LLM-assisted reviews, and debugging assistants, using real team workflows. Create and maintain prompt libraries, workflow templates, and integration guides tailored to team needs. Improve CI/testing feedback and signals with the goal of reducing flaky tests and streamlining failure triage. Lead onboarding sessions and regular Q&A meetings to share knowledge about new tools. Define and track metrics like PR cycle time, review turnaround, regression triage time, and CI flakiness, iterating based on findings and team feedback. Stay current on developments in the AI tooling ecosystem and keep the team informed about relevant updates. Requirements At least 3 years of experience in software engineering. Hands-on experience with LLM-based coding tools (such as GitHub Copilot, Cursor, Claude Code, or Codex). Strong understanding of software development workflows from an engineer’s perspective. Ability to quickly evaluate new tools and provide practical guidance to the team. Preferred qualifications Bachelor’s degree in Computer Science or a related field.