Senior Staff Engineer

About the Role
We are looking for a Senior Staff Engineer (AI Developer InfraSec Automation) to design, develop, and deploy AI-powered solutions that enhance infrastructure security workflows. You will build production-grade LLM applications using Python, orchestrate RAG pipelines with vector databases, integrate with SIEM platforms like Microsoft Sentinel/Splunk, and implement robust Cloud Security Posture Management controls. Key Requirements
- 7.5+ years of experience in software engineering, AI/ML development, or applied AI.
- Strong expertise in Python (FastAPI/Flask), asynchronous programming, testing frameworks, and package management.
- Hands-on experience with LLM providers (OpenAI, Azure OpenAI, Anthropic) and orchestration frameworks (LangChain, LangGraph). - Proficiency in Prompt Engineering, JSON schemas, function calling, and AI tool orchestration. - Practical implementation of RAG pipelines using embeddings, chunking strategies, and vector databases (Pinecone, FAISS, Chroma, etc.). - Experience evaluating LLM performance with frameworks like RAGAS, DeepEval, or LangSmith.
- Working knowledge of Java for backend services and basic frontend skills (HTML/CSS/JS). - Strong understanding of Linux, Shell scripting, Docker, CI/CD, Git, and deployment practices. - Familiarity with major cloud platforms: Microsoft Azure, AWS, or Google Cloud Platform. Security & AI Safety Focus
- Deep understanding of infrastructure security (vulnerabilities, patch management, IAM, logging). - Knowledge of AI safety concepts: prompt injection prevention, hallucination mitigation, data privacy, bias reduction.
- Experience integrating with SIEMs and writing queries in KQL/SPL. - Familiarity with CSPM, WAF, NSGs, and IaC tools like Terraform/Bicep. Responsibilities
- Design AI automation for vulnerability summarization, log analysis, remediation recommendations, and policy reviews.
- Build LLM-powered assistants using advanced prompt engineering and function calling.
- Develop scalable REST APIs in Python/Java to support internal dashboards.
- Implement responsible AI practices including PII masking, output filtering, and audit logging. - Automate operational activities like data preparation, embedding refresh, and health monitoring. Qualifications
- Bachelor's or Master's degree in Computer Science, IT, Engineering, or related field.
- Professional certifications (CISSP, CEH, CCSP, Azure/AWS/Google ML certs) are an added advantage.