Software Engineer (Backend)
Indexed description
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.
- 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.
- 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.
- 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.
- Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.
- Leverage containerization (Docker, Kubernetes) for efficient deployment and management.
- Develop and execute unit, integration, and performance tests for AI-driven systems.
- Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.
- 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.
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.
- 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.
- 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.
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