Reindeer AI

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup building our Founding Solutions Engineering team to help build and own our enterprise customer motion from the ground up. This role is perfect for a hands-on, technically deep builder who thrives in fast-moving environments, enjoys making things work in the real world, and partners closely with founders, Product, and R&D to deploy and scale complex, AI-driven enterprise solutions. You will own the technical side of the post-sale customer journey, from deployment and integration through adoption, expansion, and ongoing success, while helping define how our delivery function evolves as we grow. Your Impact Customer Onboarding & Process Analysis • Engage with customers post-close to understand workflows, operational processes, and deployment requirements. • Translate findings into clear implementation plans for AI-powered solutions. Data, AI Models & Workflow Development • Partner with customers to assess data readiness and gather inputs for AI workflows. • Configure and integrate AI components into tailored, AI-driven workflows. • Collaborate with R&D to close data gaps and extend product capabilities when needed. Deployment & Proof of Value • Own end-to-end solution deployment and ensure models meet performance and business value expectations. • Define success metrics and drive adoption post-launch. Integration, Security & Rollout • Lead integrations with enterprise systems (e.g., Finance, ERP, email platforms), ensuring scalability and security. • Guide customers through security, compliance, and IT approval processes. • Plan and execute rollout to drive smooth implementation and adoption. What It Takes • 7+ years of experience in Implementation Engineering, Solutions Engineering, Technical Consulting, Professional Services or a similar post-sale customer-facing role. • Experience in the enterprise segment, specifically within the Israeli market, preferably in traditional industries such as financial services, insurance, and banking. • Strong analytical skills with the ability to translate business needs into technical solutions. • Strong understanding of AI concepts and their enterprise applications. • High adoption of modern AI tools and workflows. • Experience supporting deployments across cloud environments and enterprise system integrations. • Excellent communication and stakeholder management skills. • Demonstrated ability to manage solution delivery across the full post-sale customer lifecycle. • Excellent Hebrew proficiency (daily client communications are in Hebrew) Nice to Have • Experience with process mining, workflow mapping, or operational analytics • Familiarity with enterprise platforms • Financial services industry experience

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team. The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows. You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations. Your Impact AI Agent Development • Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows. Workflow Automation • Build machine learning pipelines to automate content-heavy processes for enterprise businesses. Model Optimization • Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy. Collaboration • Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations. Evaluation & Testing • Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios. What It Takes Experience • 5+ years of experience as a software engineer or data scientist building production systems. • 2+ years of experience with large language models and NLP techniques. • Background in developing AI agents for content heavy tasks. • Experience with multiple LLM Vendors, RAG or Fine Tuning OSS or Commercial models. Technical Skills • Proficiency in Python and machine learning libraries such as TensorFlow or PyTorch. • Deep understanding of LLM architectures and NLP applications like entity recognition, document classification, and summarization. • Experience with model grounding techniques, retrieval-augmented generation (RAG), and deploying robust AI models in production environments. • Skills in designing and deploying AI models through APIs, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure). • Understanding of best practices for continuous monitoring, evaluation, and iterative improvement of deployed models.

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production. Your Impact Infrastructure & Platform • Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems. • Build and scale the backend systems that support high-throughput document processing and data extraction workloads. Cloud Infrastructure and Scalability • Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency. • Own containerization and orchestration (Docker, Kubernetes) for all production workloads. • Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things. Data Infrastructure • Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale. • Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM). API & Systems Integration • Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software. • Design for reliability: retries, observability, and graceful degradation across distributed systems. Security and Compliance • Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems. • Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure. Monitoring and Optimization • Build observability and monitoring systems to track infrastructure health, performance, and cost. • Continuously optimize system performance for speed, reliability, and cost-efficiency at scale. Collaboration • Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability. • Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy. What It Takes Experience • 5+ years of experience in backend or infrastructure engineering, ideally supporting production AI/ML systems or high-throughput data pipelines. • Proven track record of building and scaling infrastructure in production environments. Technical Skills • Proficiency in Python. • Databases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (e.g. Document DB, Vector DB). • Cloud: Deep experience deploying and scaling large production applications on AWS, GCP, or Azure. • Containerization and orchestration: Docker, Kubernetes. • Security: Strong understanding of OAuth2, JWT, and best practices for securing distributed systems. Nice To Have • Experience with RPA (Robotic Process Automation) tools. • Familiarity with graph databases (Neo4j) for managing complex workflows. • Familiarity with Go and Rust. • Experience working alongside AI/ML teams using frameworks like TensorFlow, PyTorch, or Hugging Face.

We’re building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn’t just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That’s where this role comes in. We are a well-funded, early-stage startup looking for a Frontend Engineer to join our team. You’ll own the experience our customers see and use every day, turning powerful AI agents into a product that feels simple, intuitive and beautiful. If you’ve shipped a customer-facing platform, care about every pixel and interaction, and believe great UX is what makes complex technology usable, we’d love to meet you. This is an opportunity to shape the look, feel and user experience of a next-generation AI platform used by large enterprises, from the very first version. Your Impact Product & User Experience • Own the frontend of our customer-facing platform, from first concept to production. • Build modern, polished and responsive interfaces that let users interact seamlessly with AI agents and automated workflows. • Create dashboards, workflow builders and visualization tools that make complex AI processes clear, trustworthy and easy to follow in real time. • Bring a sharp eye for UX/UI, catching the details that turn a working feature into a great experience. • Partner closely with product and design to translate complex AI capabilities into simple, elegant user flows. • Use customer feedback and real usage to continuously improve the product experience. Frontend Engineering • Build a scalable, high-quality frontend architecture and a reusable component system. • Handle real-time updates, event streams and notifications so users always know what their agents are doing. • Present AI-generated data in clean, user-friendly formats and visualizations. • Work with backend APIs (REST/GraphQL) and contribute to the API layer when needed. Team Collaboration & Culture • Work closely with AI engineers, product designers and enterprise customers to align the product with real business needs. • Participate in code reviews, architecture discussions and feature planning. • Help shape our engineering culture and set the bar for product quality as part of the founding team. What It Takes Experience • 5+ years of frontend engineering experience. • Proven track record building and shipping customer-facing products or platforms used by real users in production. • A strong eye for design and UX, with a portfolio or examples of products you’re proud of. • Experience in early-stage startups or data-heavy / AI-driven products is a big plus. Technical Skills • Deep expertise in React (Svelte is a bonus) and TypeScript. • Strong command of JavaScript, HTML and CSS, including responsive design, animations and accessibility. • Experience building design systems or component libraries. • Experience with data visualization and real-time UIs. • Good understanding of REST/GraphQL APIs. Node.js experience is a plus. • Familiarity with CI/CD, testing and frontend performance optimization.

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments. Your Impact AI Agent Development • Design and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management. • Implement reinforcement learning techniques to enhance decision-making capabilities of AI agents. AI Integration • Build and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM). • Use frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing. Data Processing and Pipelines • Design and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently. • Optimize data handling to improve speed and accuracy of AI agents. Security and Compliance • Implement authentication and authorization mechanisms to secure AI-driven systems. • Ensure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling. Cloud Infrastructure and Scalability • Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability. • Leverage containerization (Docker, Kubernetes) for efficient deployment and management. Testing and Optimization • Develop and execute unit, integration, and performance tests for AI-driven systems. • Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency. Collaboration • Work closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements. • Participate in code reviews, design discussions, and architecture planning to drive innovation. What It Takes Experience • 5+ years of experience in software engineering with a focus on AI-driven or autonomous systems. • Proven track record of deploying AI models or agents in production environments. Technical Skills • Proficiency in Python. • Databases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (e.g. Document DB, Vector DB). • Cloud: Experience deploying large scale production applications on AWS, GCP, or Azure. • Security: Understanding of OAuth2, JWT, and best practices for securing systems. Nice To Have • AI Frameworks: Experience with TensorFlow, PyTorch, or Hugging Face. • Experience with RPA (Robotic Process Automation) tools • Familiarity with graph databases (Neo4j) for managing complex workflows. • Familiarity with Go and Rust • Experience with CI/CD pipelines and DevOps practices.