Artificial Intelligence Engineer

Job Responsibilities

• Research and develop AI-powered solutions based on defined requirements and technical designs.
• Build and enhance cybersecurity tools and processes—including Cyber Detection, Response, and Recovery (CDRR) systems—using AI/ML.
• Contribute to the creation of documentation, support procedures, and operational runbooks for handoff to SRE and operations teams.
• Enforce secure software development lifecycle (SDLC) best practices throughout the development process.
• Continuously investigate emerging technologies and methods to improve system resilience, presenting findings for architectural review.

Job Requirements

• 3 -10 years’ experience with Generative AI and LLM techniques (e.g., fine-tuning, distillation, Retrieval-Augmented Generation, Model Compression/Pruning (MCP), Agent-to-Agent communication (A2A)).
• Solid understanding of AI/ML fundamentals and algorithmic models. Experience with AI/ML frameworks such as PyTorch, LangChain, or similar.
• Experience in data processing and proficiency in Python programming are essential.
• Familiarity with test-driven development (TDD).
• Hands-on experience with CI/CD tools (e.g., Git, Jenkins, TeamCity).
• Experience working with databases (RDBMS, NoSQL, or graph databases).
• Scripting experience using Shell, Regular Expressions, etc.
• Working knowledge of Linux environments
• Experience with Agile methodologies (e.g., sprint planning, stand-ups, retrospectives).
• Exposure on infrastructure tools and platforms such as Docker, Kubernetes, Ansible, Splunk for security observability, Public Cloud (e.g., AWS, Azure, GCP).
• A collaborative mindset with strong problem-solving skills.
• Excellent verbal and written communication, capable of translating technical ideas across teams.