AI Engineer

Job Description:

5–7 years of professional software engineering experience developing, deploying, and supporting enterprise applications.

· 2+ years of hands-on experience with AI technologies, including LLMs, AI agents, generative AI applications, RAG architectures, or AI-powered automation solutions.

· Bachelor's degree in Computer Science, Cybersecurity, Information Systems, Software Engineering, or a related technical discipline, or equivalent practical experience.

· Strong programming experience in Python, Go, Rust, JavaScript, or similar development languages.

· Experience with cloud-native development, APIs, containers, Kubernetes, CI/CD pipelines, and Git-based development workflows.

· Solid understanding of secure coding principles, application security fundamentals, and common vulnerability classes.

· Strong analytical, troubleshooting, and problem-solving skills.

· Excellent written and verbal communication skills with the ability to work effectively across technical and business teams.

· Ability and willingness to work a flexible schedule, including occasional late-night deployments, production support activities, incident response efforts, maintenance events, and on-call responsibilities as business needs require.

· Demonstrated ability to rapidly learn, adopt, and effectively utilize new technologies, tools, frameworks, and platforms in a fast-paced engineering environment.

· Strong commitment to continuous learning and professional development across software engineering, artificial intelligence, cybersecurity, and cloud technologies.

Preferred Qualifications

· Experience building and deploying enterprise AI applications or agentic AI systems in production environments.

· Background in application security, cybersecurity engineering, penetration testing, red teaming, vulnerability management, or DevSecOps.

· Hands-on experience identifying and mitigating AI security risks such as prompt injection, data leakage, model manipulation, and agent misuse.

· Experience with AI frameworks and platforms such as OpenAI, Azure AI, Anthropic, LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar technologies.

· Familiarity with vector databases, AI evaluation frameworks, and RAG architectures.

· Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform preferred).

· Experience implementing security controls within software development lifecycles and cloud environments.

· Proficiency with AI-assisted engineering tools such as GitHub Copilot, Cursor, Windsurf, VS Code Agent, or similar tools.

· Demonstrated ability to drive innovation through automation, experimentation, and engineering excellence.

Education

· Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Artificial Intelligence, Data Science, Information Systems, or a related technical field.

· Master's degree in Computer Science, Artificial Intelligence, Cybersecurity, or a related discipline is preferred but not required.

· Relevant professional certifications are highly desirable:

o Certified Secure Software Lifecycle Professional (CSSLP)

o Certified Information Systems Security Professional (CISSP)

o GIAC Security Certifications

o AWS, Azure, or Google Cloud certifications

o AI, Machine Learning, or Generative AI certifications from recognized providers