About This Role
This engineering role focuses on both AI/ML software development and cybersecurity, requiring a hands-on professional who can manage the entire software lifecycle. The position balances AI integration, debugging, deployment, infrastructure, and security tasks, with strong practical knowledge expected in both domains.
Responsibilities
- Develop and integrate AI/ML, LLM, RAG, and automation-based applications
- Work with LLM APIs, embeddings, vector databases, document processing, and AI workflows
- Build backend services, APIs, database systems, and background/automated processes
- Understand system architecture, service-to-service communication, and scalable application design
- Work with Git, Docker, Linux, Redis, and cloud/server environments
- Debug application, API, database, integration, and production issues independently
- Write clean, maintainable, testable, and secure code
- Evaluate AI outputs and improve accuracy, reliability, performance, and cost
- Understand when to use traditional programming, databases, search, ML, or LLMs for a particular problem
- Identify and fix common vulnerabilities such as SQL injection, XSS, SSRF, CSRF, IDOR, and insecure file handling
- Secure APIs, databases, containers, credentials, secrets, and internal services
- Perform security-focused debugging, log analysis, and root-cause investigation
- Implement appropriate logging, auditing, monitoring, access controls, and data protection
Requirements
- Strong hands-on experience with Python, FastAPI, REST APIs, and SQL/PostgreSQL
- Strong understanding of OWASP Top 10 and application/API security
- Experience with authentication, authorization, RBAC, JWT/session security, and access control
- Understand networking, Linux, servers, firewalls, HTTPS/TLS, and secure deployments
- Basic understanding of cloud security, IAM, Docker security, and infrastructure hardening
- Understand AI/LLM security, including prompt injection, data leakage, insecure tool usage, and RAG security
- Strong problem-solving and debugging skills
- Able to understand an existing codebase and work across multiple technologies
- Capable of taking a feature from requirement architecture development testing security deployment maintenance
- Comfortable working with both application-level and infrastructure-level problems
- Understand the generated code from AI coding assistants and independently debug and verify it
- Strong fundamentals in AI are more important than simply knowing a large number of AI tools or frameworks
Nice to have:
