Key Responsibilities

• Lead the engineering team, manage sprint planning, code reviews, mentoring, and technical delivery.
• Design and manage the SecureAI platform and Application Security (AppSec) developer portal.
• Develop AI-powered security solutions using LLMs, RAG pipelines, and agentic AI frameworks.
• Build secure backend services, APIs, microservices, and security data ingestion pipelines.
• Manage Azure, GCP, and AWS cloud infrastructure, Kubernetes, and cloud security controls.
• Implement CI/CD, MLOps, model monitoring, deployment automation, and production reliability.
• Integrate security tools such as SIEM, EDR/XDR, SAST, SCA, and CSPM platforms.
• Ensure compliance, access control, data protection, incident response, and security standards.

Required Technical Skills

• Programming: Python, Java/Go (preferred).
• AI/ML: LLMs, Prompt Engineering, RAG, LangChain, LangGraph, Semantic Kernel.
• Backend: FastAPI, Django/Spring Boot, Microservices, REST APIs, OAuth 2.0/OIDC, RBAC/ABAC.
• Cloud: Azure (primary), GCP, AWS, Azure OpenAI, Azure ML.
• DevOps/MLOps: Kubernetes/AKS, Docker, CI/CD, GitOps, MLflow, ArgoCD/Flux.
• Security: CSPM, SIEM/SOAR, MITRE ATT&CK, Threat Modeling, Zero Trust, ISO 27001, NIST CSF.

Required Experience

• 6–8 years of software engineering experience, including at least 1 year in AI/ML systems.
• Strong backend development, cloud platform engineering, and Kubernetes experience.
• Proven technical leadership, team mentoring, architecture design, and delivery management.

Preferred Certifications

Azure Solutions Architect Expert, Azure AI Engineer, AWS Solutions Architect Professional, GCP Professional Cloud Architect, CISSP, CCSP, CEH, or SC-200.