Hire Jay N. - Forward Deployed Engineer

* Embedded within enterprise client environments as the single point of technical accountability for AI-assisted database modernization — translating legacy DB2 (LUW/z/OS) and Oracle estates into cloud-native PostgreSQL on AWS using the DataCat Catalyst Suite. * Own each engagement end-to-end: source readiness profiling, DDL capture, PL/SQL conversion-risk triage, schema conversion, parallel-run orchestration, and cutover execution — translating executive objectives into engineering plans across infrastructure, application, and data teams. * Apply LLM-assisted tooling for migration validation, incident analysis, and data-pattern discovery — meaningfully reducing manual effort and risk during high-complexity cutover phases. * Establish SLO/SLI reliability baselines for PostgreSQL workloads from day one, operationalizing SRE practice at the data platform layer the moment production cutover completes. * Deliver complete client operational independence — migration runbooks, stabilization playbooks, and handoff documentation that eliminate ongoing vendor dependency. * My focus: moving teams from "we are migrating systems" to "we are modernizing how systems are built, observed, and operated."

* 1. Platform Engineering & Kubernetes * Designed and implemented GitOps-based deployment architecture using ArgoCD for multi-environment Kubernetes management * Automated cluster provisioning and application deployment using Ansible playbooks and infrastructure-as-code patterns * Built event-driven remediation workflows where monitoring alerts triggered automated recovery actions * Standardized Kubernetes cluster configurations to ensure consistent environment parity across staging and production systems * Managed containerized microservices and autoscaling workloads running on AWS EKS * 2. CI/CD & DevOps Automation * Built and optimized CI/CD pipelines using Jenkins integrated with Ansible automation * Enabled zero-downtime deployments and faster release cycles across distributed applications * Supported deployment workflows for .NET and microservice-based applications using version-controlled pipelines (GitHub/GitLab Actions) * Improved release velocity while maintaining production stability and rollback safety * 3. Observability, Reliability & SRE Practices * Implemented full-stack observability using Prometheus, Grafana, ELK stack, CloudWatch, and Splunk ITSI * Built unified dashboards for proactive system monitoring and business-level insights * Defined and enforced SLIs/SLOs (99.99% uptime targets) and structured error budgets to drive reliability decisions * Established blameless postmortems and incident review processes to improve system resilience * 4. AI-Driven Operations & AIOps * Introduced AI-assisted incident response and predictive alerting using AIOps tools (Dynatrace Davis, AppDynamics, and custom LLM-based agents) * Reduced MTTR by 30–60% through automated alert correlation and root cause analysis assistance * Developed early-stage automation for runbook generation and incident summarization using machine learning and LLM workflows * Improved operational efficiency by reducing manual triage and alert fatigue

Directed Level 2 NOC operations for a major logistics client (Kar Auction Services), coordinating onshore/offshore (US/Bangalore) teams to standardize ITIL-based incident and problem management — achieving measurable improvements in SLA adherence within the engagement. Deployed enhanced monitoring tooling (Nagios/ELK), led incident bridge calls and escalations, and built the RCA process library and team knowledge base that remained in use after the engagement concluded.