Agent Ai Engineer Jobs

About Zinnov Zinnov is a global management consulting firm that helps organizations make decisions that actually get used — and deliver results that matter. For over two decades, we’ve partnered with leading enterprises, high-growth technology companies, and investors to answer some of the toughest questions they face: Where should we invest? How do we scale globally? What capabilities will win in the next decade? Our work shapes market entry strategies, global operating models, M&A decisions, and long-term growth bets. We’re known for being data-led, execution-focused, and outcome-driven — not opinion-heavy slideware. At Zinnov, how you work matters as much as what you deliver. We value independent thinking, crisp communication, and early ownership. With 450+ professionals across 10 global offices, we work across industries including Digital Services, ER&D, Enterprise Software, Semiconductors, Healthcare, BFSI, Automotive, Media & Telecom, and Private Equity. Zinnov isn’t for everyone. It’s for people who want steep learning curves, honest feedback, and the chance to see their work influence real business decisions — not just presentations. About the Role As an Agent / AI Engineer , you will build the AI layer of the GCC Intelligence Platform—the conversational agent users interact with. You will own grounding, retrieval, persona routing, session state, and permission-aware querying so the agent stays accurate, secure, and tenant-safe. What You’ll Do LLM & Agent Integration Integrate LLM APIs (e.g., AzureOpenAIor equivalent) for conversational workflows. • Build a grounding layer that anchors responses to real platform data (not model guesses). • Maintain prompt templates across multiple personas and use-cases. Retrieval, Permissions & Security Boundaries Implement intent classification and persona routing to the right KPI views. • Build the API

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

Who Are We? Postman is the world’s leading API platform, used by more than 45 million+ developers and 500,000 organizations, including 98% of the Fortune 500. Postman is helping developers and professionals across the globe build the API-first world by simplifying each step of the API lifecycle and streamlining collaboration—enabling users to create better APIs, faster. The company is headquartered in San Francisco and has offices in Boston, New York, Austin, Tokyo, London, and Bangalore - where Postman was founded. Postman is privately held, with funding from Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. Learn more at postman.com or connect with Postman on X via @getpostman. P.S: We highly recommend reading The "API-First World" graphic novel to understand the bigger picture and our vision at Postman. The Opportunity (Summer 2026 AI Internship - Applications Open Now) We're seeking an AI Engineer Intern to work alongside our AI team on large-scale AI and Agentic systems from data pipeline to production deployment. This role is scoped for someone with foundational experience who wants to deepen it: you'll own discrete pieces of real systems under the mentorship of senior engineers, not shadow work or isolated coursework-style projects. What You'll Do You’ll work directly with the AI team, taking responsibility for well-scoped pieces of real systems, with mentorship from senior engineers. Benchmarks & Evaluation Contribute to APIFlow-Bench , our open-source benchmark for real API-development work: design and review benchmark tasks and their mock API environments, extend the evaluation harness and task-generation pipeline in Python, and help maintain the public multi-model leaderboard with statistical confidence intervals. Help build a new action-level AI safety benchmark: instead of grading what a model says, it scores what an agent actually does inside a simulated enterprise API environment. You’ll work on scenari

Role: Senior AI Engineer Location: Hyderabad, India (Hybrid) Department: Product Development About the Role GHX is building a cutting-edge LLM-powered document understanding platform focused on classification, structured data extraction, and intelligent orchestration at scale. This is a high-impact AI engineering role where you will own the full lifecycle—from problem framing to production deployment . Initially, you will focus on prompt engineering and evaluation systems , building the quality foundation for AI performance. Over time, the role expands into agent orchestration, system architecture, and migration of rule-based systems to LLM-driven pipelines . A strong foundation in software engineering (5+ years) is essential. This role demands engineering rigor across both traditional system design and AI system behavior . Core Responsibilities 1. Prompt Engineering Design prompts for diverse document classification and extraction tasks Treat prompts as formal specifications (precise, structured, and edge-case-aware) Develop few-shot, chain-of-thought, and structured output templates Manage prompt lifecycle: versioning, testing, and rollback 2. LLM Output Evaluation Create and maintain ground truth datasets Build automated evaluation pipelines (precision, recall, field-level accuracy) Identify and resolve conceptually incorrect outputs despite surface correctness 3. AI Agent Orchestration Design multi-agent workflows for document processing Implement tool-use patterns and integrate MCP servers Optimize orchestration for scale and efficiency 4. Software Engineering Develop production-grade APIs and backend services Apply Clean Architecture / DDD principles Write maintainable, testable Python code Contribute to CI/CD, deployment, and observability systems 5. Stakeholder Collaboration Act as a bridge between business stakeholders and AI systems Translate product requirements into technical architectures Communicate system behavior, limitations, and quality

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior AI Engineer, you'll join a 10-person team focused on data integrations (shippers and carriers moving in and out of the FourKites ecosystem) and our active AI agent workstreams — including a support automation agent handling 60-70% of customer tickets, a voice agent that calls carriers to gather and update information, and an end-to-end carrier onboarding agent (email + voice). You'll work on features end to end (~75-80% backend, ~20-25% frontend) using Python, Java/GoLang, agentic frameworks like LangGraph, React, Redis and PostgreSQL. You'll develop products that change the logistics landscape for some of the biggest corporations in the world, and work closely with our US team and customers to shape the future of the industry. What you’ll be doing: Design, build, and productionize AI agents/workflows (e.g., support automation, voice, and onboarding agents) using agentic frameworks such as LangGraph Develop, test, and maintain backend applications in Python and Java or GoLang Write clean, efficient, and well-documented code across the full SDLC — development, QA, and release Design and implement data models and database schemas Collaborate with the frontend team to integrate the backend with the user interface Perform code reviews and ensure code quality standards are met Troubleshoot and debug applications, including AI agent workflows in production Work with the DevOps team to deploy and manage applications in production (Kubernetes) Continuously learn and stay up to date with new technologies and industry trends, particularly in the AI/agentic space About the team: Our

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

We're Hiring Senior AI Engineer (Generative AI Azure) Remote Immediate Joiners Preferred Salary: Up to 12 LPA We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions on Microsoft Azure. The ideal candidate will have strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Azure AI Services, and modern AI engineering practices. Technical Summary • AI & LLMs: Azure OpenAI, GPT-4.x, OpenAI, Prompt Engineering, Prompt Chaining, Function Calling, Structured Outputs, Tool Calling, JSON Schema, Model Evaluation, Guardrails, Fine-tuning Concepts • Agentic AI: Multi-step Reasoning, Planning, Memory Management, Tool Orchestration, Multi-Agent Systems, Human-in-the-Loop Workflows, Reflection, Context Management, AI Observability • Frameworks: Semantic Kernel, LangChain, LangGraph, AutoGen, Azure AI Agent Service • RAG & MCP: Retrieval-Augmented Generation, Vector Search, Semantic Search, Hybrid Search, Embeddings, Knowledge Grounding, Citation Generation, Document Ingestion, Chunking, MCP Architecture, MCP Servers & Clients • Azure Technologies: Azure AI Foundry, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning, Azure Functions, API Management, Logic Apps, App Service, Container Apps, AKS, Azure Storage, Data Lake Gen2, Azure Key Vault, Azure Entra ID, Azure Monitor, Application Insights, Event Grid, Service Bus • Programming & DevOps: Python, C#, REST APIs, FastAPI, ASP.NET Core, JSON, YAML, Git, Azure DevOps, Docker, Kubernetes • Data Platforms: SQL Server, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, Microsoft Fabric, Azure Databricks, Delta Lake, Vector Databases (Azure AI Search, Pinecone, Weaviate, Milvus, Qdrant) • Security & Governance: Responsible AI, Prompt Injection Prevention, RBAC, Content Filtering, Data Privacy, GDPR, ISO 27001, Azure Key Vault, Audit Logging & Monitoring • Nice to Have: Microsoft Copilo

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the Role: As a Forward Deployment Architect, you will serve as a hands-on senior technical architect on the Applied AI Engineering team, owning the end-to-end design and delivery of AI-driven business transformation projects. You'll work closely with pre-sales teams to scope technical integration and implementation strategies, translating business requirements into architectural solutions. Once opportunities move to post-sales, you'll own the detailed technical designs from original scoping documents and drive execution including hands-on coding to build proofs-of-concept, custom integrations, and solution prototypes that validate technical feasibility. As the technical owner of the customer relationship, you'll partner cross-collaboratively to ensure successful delivery. Your role spans from understanding domain-specific customer needs to architecting scalable, agent-based AI solutions using DevRev's platform**, with direct involvement in implementing key technical components and debugging complex integration challenges. This position requires a unique blend of enterprise architecture expertise, AI solution design, hands-on development skills, customer empathy, and cross-functional collaboration. You'll act as

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. We are looking for a technically-capable product leader to head up AI Design at Fin. Fin is the #1 AI agent for customer service — a full-stack, vertically integrated AI system powered by our own in-house models, Apex, designed specifically for customer experiences. The role is to lead the Design function within our AI Group, where our custom models and core Fin functionality are developed. You will be managing our AI Designers (currently 3 Staff/Principal level AI Designers). You will work directly with AI Engineers and Scientists in our AI Group , and Product Designers and teams in our R&D group. We believe that leading AI Design is a new type of product leadership role that combines technical, product, and leadership qualities. This includes shaping how the Fin AI models and harness behave — how they reason, respond, and improve over time. The experience is defined as much by model behavior, evals, and iteration loops as it is by UI. We’re looking for someone to lead in that world.

Team description At Datadog, AI agents are becoming first-class consumers of observability, security, and software delivery data — from third-party coding agents like Claude Code, Cursor, and Copilot, to our own Bits SRE, Bits Assistant, and Bits Dev Agent. The Agentic Interfaces team owns the platform that connects these agents to Datadog: the MCP Server, the tools and retrieval surfaces agents call into, and — critically — the evaluation systems that tell us whether an agent's experience on Datadog data is actually getting better over time. This role is about that last piece. We're hiring a Staff Applied Scientist to define what "good" means for an Agentic interface at Datadog and to build the measurement systems that make it true. "Good" isn't one number — it spans answer quality, tool-selection accuracy, retrieval relevance, latency, token cost, and end-to-end agent success on real customer workflows. You'll design the evals, build the datasets, define the metrics, and partner with the AI engineers on the team to land the platform that lets every product group at Datadog ship integrations that are demonstrably better release over release. The space is full of open research questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when the tool catalog has hundreds of entries and grows weekly? How do you build a measurement system that catches regressions across first-party and third-party agents at once, without each team writing their own harness? If those are the problems you want to spend your time on, come build this with us. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. What You’ll Do: Own the evaluation strategy for Datadog's AI agent integrations. Define the metrics — offline and online, quali

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

센드버드는 옴니채널 AI와 세계 최고 수준의 검증된 커뮤니케이션 API를 결합하여, 기업이 AI 에이전트를 구축하고 의미 있는 고객 연결을 대규모로 만들어갈 수 있도록 돕습니다. 센드버드는 엔터프라이즈 수준의 안정성, 보안성, 규정 준수를 갖춘 솔루션을 제공합니다. DoorDash, Match Group, Noom, Yahoo Sports를 포함한 4,000개 이상의 글로벌 선도 앱이 센드버드를 신뢰하고 있으며, 매월 70억 건 이상의 대화가 센드버드 플랫폼을 통해 이루어지고 있습니다. 현재까지 실리콘밸리 최정상 투자사로부터 (ICONIQ, SoftBank, Tiger Global, Y Combinator) 누적 총 2억2천만달러 (약 2,450억 원)의 투자를 유치하였으며 국내 최초 기업가치 1조원 이상의 글로벌 유니콘 기업입니다. 캘리포니아 산 마테오의 본사와 서울의 R&D센터 및 APAC 오피스 그리고 뉴욕, 런던, 싱가포르, 인도, 캐나다 등에 오피스를 두고 있습니다. Intern, AI Agent Engineering AI 에이전트 엔지니어링 인턴은 엔지니어링 및 제품 팀과 협력하여 지능형 에이전트를 구축, 통합 및 배포합니다. 최신 웹 프레임워크, LLM API 및 툴링 파이프라인을 사용하여 프로토타입부터 프로덕션까지 실무 경험을 쌓게 됩니다. 인턴십 기간은 8~12주 입니다. 이런 일을 하실 수 있어요 에이전트 프로토타이핑 및 개발 프롬프트 엔지니어링으로 Hallucination 탐지, 대화 Resolution 등 마이크로 API 개발업무를 합니다. 내부 데이터셋과 도구를 활용해 AI Agent의 정확도를 테스트하고 검증합니다. 검색 증강 생성(RAG), 지식 기반 및 맞춤형 툴체인을 지원하는 백엔드 API를 통합합니다. 프롬프트 엔지니어링 및 툴링 다양한 사용 사례에 맞는 프롬프트를 제작, 테스트 및 세부 조정합니다. 프롬프트 버전 및 에이전트 배포를 위한 CI/CD 파이프라인을 설정합니다. 통합 및 배포 웹, 채팅 및 API 중심 환경에 에이전트를 임베드합니다. 실시간 성능 지표를 모니터링하고 로그, 대시보드 등의 관측 기능을 구현합니다. 협업 및 문서화 팀이 시니어 엔지니어, 제품 관리자 및 UX 디자이너와 긴밀히 협력할 수 있도록 지원합니다. 이런 분과 함께 하고 싶어요 Python: 깔끔하고 유지 관리가 용이한 Python 코드 작성 경험 Backend: Django, FastAPI, Express 등 서버 측 프레임워크를 사용한 백엔드 개발 실무 경험 협업: 뛰어난 의사소통 능력, 문서화 기술, 그리고 애자일한 팀에서의 협업 경험 이런 점이 있으시면 더 좋아요 프롬프트 엔지니어링 프레임워크(예: LangChain) 사용 경험 클라우드 플랫폼(AWS Lambda, Vercel, GCP Cloud Functions)에 대한 이해도 AI 제품 관련 UX 디자인 또는 제품 관리 경험 Django 또는 유사한 Python 웹 프레임워크 사용 경험 이런 점을 얻을 수 있어요 첨단 에이전트 기반 AI 개발 및 시스템 배포에 대한 심층 분석 엔지니어링, 제품 및 디자인 전문가와의 교차 기능 협업 시니어 AI 엔지니어의 멘토링 및 정규직 전환 기회 실제 고객 사용 사례, 성능 튜닝 및 프로덕션급 툴 활용 경험 유연근무제 정책 Sendbird는 유연한 근무 일정을 지원합니다. 협업과 팀워크의 중요도가 높기에, 모든 구성원은 주 3일 이상 사무실에서 함께 모여 일하고 있어요. 일부 역할은 사무실 출근이 더 자주 필요할 수 있으니, 구체적인 요건은 매니저와 상의해 주세요. 센드버드가 생각하는 다양성과 포용 위 요구사항에 100% 부합하지 않으셔도 괜찮습니다. 센드버드는 모두가 배우고 성장할 수 있는 곳이기에 다양한 배경, 경험 및 기술 스택을 가진 누구든 최고의 직원이 되실 수 있다고 생각합니다. 우리는 평등한 고용 기회를 위해 다양성을 존중하고 장려하고 있습니다. 이 포지션이 여러분의 가슴을 뛰게 만든다면 지원해주세요! Flexible Work Policy We offer

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Backend Engineer on the GitLab Agent Observability team, you'll go beyond using AI tools and help define how we design, build systems that allow AI agents to interact with the full software delivery lifecycle, way beyond pure code creation. In this role you’ll contribute to the development of complex features and help establish architectural patterns both for how to interact with AI Agents across GitLab and how the resulting AI contributions manifest across GitLab. You’ll collaborate closely with engineers across the Agent Foundations stage and adjacent teams within AI engineering. This is a hi

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+ AI Infrastructure Engineers to build the systems that train and serve Fin's next generation of AI products. Fin is an AI company that builds from the GPU all the way up to a user agent that resolves millions of customer service queries a month. You’ll join a small, highly technical team working at the cutting edge of modern AI infrastructure. The AI Infra team built the training pipelines and runs the inference for custom models like Fin Apex, which outperforms frontier models in customer service tasks, and is the foundation of the AI Group's full stack approach to AI. We’re particularly interested in engineers who have: A track record of working on model training or model inference at scale , or on low‑level GPU coding (e.g. CUDA, Triton). Experience with one is great, multiple is even better. What will I be doing? As a Senior AI Infrastructure Engineer focused on model training and inference, you will: Implement and scale training pipeli