Jobs at SRM Technologies

Monitors network, cloud, server, endpoint, and security environments in a 24x7 rotational operation. Performs initial triage and troubleshooting of infrastructure and security alerts, analyzes SIEM and security tool events, manages incidents through ITSM platforms, escalates critical issues, supports incident response and service restoration, and maintains documentation, reports, and shift handovers.

Performs advanced security monitoring, incident response, threat hunting, malware and forensic analysis, SIEM detection engineering, and cloud security investigations. The analyst escalates and coordinates major incidents, tunes detection rules, analyzes endpoint and cloud threats, supports ransomware response, and improves cyber defense capabilities. The role participates in 24/7 coverage, on-call support, and major incident management.

Provides advanced 24x7 operational support for network, cloud, security, and infrastructure services. Responsibilities include resolving high-priority incidents, troubleshooting routing, firewalls, VPNs, Zscaler, Azure, and AWS, conducting root cause analysis, managing changes, coordinating vendors, monitoring capacity and availability, mentoring L1 analysts, and maintaining technical runbooks. Leads major incident resolution and participates in on-call and maintenance activities.

Lead backend architecture and system design for distributed systems. Build high-performance Python/FastAPI services, RESTful and async APIs, design RDBMS and NoSQL schemas, ensure scalability, resilience, and maintainability, produce architecture docs, and guide teams on trade-offs and best practices.

Provide statistical expertise for clinical trial design, analysis, and reporting. Develop SAPs, randomization schemes, TLFs, SDTM/ADaM datasets, and define.xml. Program and validate analyses in SAS, R, and Python; create dashboards, Spotfire visualizations, and automated reports. Ensure CDISC/ICH compliance, support regulatory submissions, safety analytics, RBM, and present findings cross-functionally.

Build and deploy ML models on structured and unstructured data, design A/B tests, create visualizations, collaborate cross-functionally, operationalise pipelines with data engineering, develop domain expertise, and translate analyses into stakeholder recommendations.

Design, build, and deploy enterprise-scale Agentic AI and multi-agent systems, LLM fine-tuning and RAG pipelines, vector search, AI copilots, and production AI microservices. Lead model development, MLOps/CI-CD, cloud integration (Azure/AWS/GCP), monitoring, governance, and deliver measurable automation and business outcomes.