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.