תיאור המשרה
We are a well-funded, early-stage startup seeking 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. Key Responsibilities: 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. Qualifications: 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. Bonus Skills: 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.
על Reindeer
Reindeer is an AI platform that deploys and manages intelligent agents for complex, human-intensive workflows across the enterprise. We help teams move from “AI that answers” to AI that reliably executes work inside real business processes, with clear accountability and governance.
Reindeer is built for environments where accuracy, auditability, and repeatability matter: unstructured inputs, multi-step decisioning, handoffs across functions, and systems that can’t be ripped and replaced. Our agents operate within existing tools and workflows, extracting and structuring information, identifying gaps, routing for review when needed, and maintaining end-to-end visibility so teams can trust outcomes at scale.
To keep performance consistent over time, Reindeer uses human-in-the-loop training and workflow-grounded feedback loops to eliminate drift and hallucinations, and continuously improve reliability as edge cases appear. This approach enables enterprises to scale AI adoption safely, without turning every new use case into a bespoke project.
The result is faster cycle times, fewer manual touchpoints, and more consistent execution across teams while keeping humans in control where it matters most.
We've successfully automate workflows like payment approvals, quote management, and document processing for Fortune 100 companies.