Senior Staff Engineer (AI Developer SOC Automation)

Job description

**Company Description** **We're Nagarro.** We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! **Job Description** **Requirements** - Experience : 7.5+ years - Strong experience in software engineering, AI/ML development, or automation engineering, including hands-on experience building AI/ML solutions. - Strong programming expertise in Python with experience using AI/ML libraries such as Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow. - Hands-on experience developing AI-powered automation using Large Language Models (LLMs), Azure OpenAI, OpenAI APIs, and prompt engineering techniques. - Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions for enterprise AI applications. - Strong knowledge of Microsoft Azure services including Azure Machine Learning, Azure Functions, Logic Apps, Azure Event Hub, and Microsoft Sentinel. - Experience developing REST APIs and microservices using FastAPI or Flask. - Hands-on experience integrating AI solutions with SIEM, SOAR, security monitoring, and ticketing platforms. - Good understanding of cybersecurity fundamentals including SIEM concepts, security monitoring, attack patterns, threat detection, MITRE ATT&CK framework, and log analysis. - Experience building AI-powered alert automation, incident response workflows, and threat intelligence solutions. - Familiarity with cloud platforms including Microsoft Azure, AWS, and Google Cloud Platform. - Working knowledge of Git, Docker, CI/CD pipelines, containerization, and modern software development practices. - Experience with Azure Sentinel Analytics Rules, Playbooks, Workbooks, or similar security automation capabilities is preferred. - Familiarity with SOAR platforms such as Microsoft Sentinel SOAR, LogRhythm SIEM, or equivalent security orchestration solutions. - Knowledge of Google Cloud services including Security Command Center, Pub/Sub, and BigQuery is an advantage. - Experience using LLM orchestration frameworks such as LangChain, Semantic Kernel, or equivalent AI frameworks is desirable. - Familiarity with Azure AI Search (Cognitive Search), vector databases, and semantic search capabilities is preferred. - Understanding of on-premises SIEM platforms and enterprise log aggregation tools is an added advantage. - Strong analytical, troubleshooting, and problem-solving skills with the ability to build scalable AI-powered security automation solutions. - Excellent communication and collaboration skills with experience working in Agile and cross-functional engineering teams. - Bachelor's degree in Computer Science, Information Technology, Engineering, MCA, or a related discipline. - Professional certifications such as Microsoft SC-200, AZ-900, CEH, CompTIA Security+, or equivalent cloud and cybersecurity certifications are desirable. **Responsibilities** - Design, develop, and maintain AI-powered automation solutions to enhance Security Operations Center (SOC) workflows, including alert classification, anomaly detection, threat prioritization, and incident response. - Build AI-powered security agents and bots that automate alert triage, investigation, and remediation processes. - Develop and fine-tune NLP and machine learning models for log parsing, alert summarization, phishing detection, Indicator of Compromise (IOC) extraction, and threat intelligence analysis. - Design and implement feature engineering pipelines to process security telemetry from cloud and on-premises monitoring platforms, including Microsoft Sentinel, GCP Security Command Center, Trend Micro XDR, and SIEM solutions. - Build and optimize Retrieval-Augmented Generation (RAG) pipelines that leverage enterprise threat intelligence repositories, knowledge bases, and security playbooks. - Develop, evaluate, and optimize LLM-powered security use cases through prompt engineering, model evaluation, and continuous performance improvement. - Develop Azure Functions, Logic Apps, and Python-based automation to streamline alert enrichment, incident routing, notification workflows, and security operations. - Build and maintain integrations with SIEM, SOAR, ticketing, monitoring, and security platforms using REST APIs, FastAPI, and custom connectors. - Integrate AI-generated insights with incident management systems to automate ticket creation, prioritization, and status tracking. - Develop Python-based APIs and microservices to expose AI capabilities for enterprise security applications. - Consume, normalize, and process event streams from Azure Event Hub, GCP Pub/Sub, cloud platforms, and on-premises log sources. - Develop unit tests, integration tests, and participate in peer code reviews to ensure secure, scalable, and high-quality software delivery. - Monitor AI model performance, detect model drift, maintain dashboards, and continuously improve model accuracy using MLOps best practices. - Maintain CI/CD pipelines for AI model deployment, automation releases, and infrastructure updates. - Prepare technical documentation including API specifications, architecture diagrams, deployment guides, operational runbooks, and data models. - Collaborate closely with SOC analysts, cybersecurity engineers, cloud teams, DevOps engineers, and data scientists to continuously improve AI-driven security automation. **Qualifications** Bachelor’s or master’s degree in computer science, Information Technology, or a related field.