pratiksha dhotre

pratiksha dhotre

pratiksha123dhotre@gmail.com

Skills
Python
Experience

Agentic AI & Observability Engineer

Accenture

Feb 2024 to Present
  • 🚀 Driving Agentic AI engineering, LLMOps observability, and cloud infrastructure at enterprise scale on Accenture's ReInvention.AI (RIAI) platform.
  • 🤖 Autonomous AI Agents & Automation:
  • • Built multi-step autonomous AI agents using AWS Bedrock (Claude) with tool calling, persistent memory, and multi-step reasoning.
  • • Developed an Automated Vulnerability Management Agent for vulnerability report scanning, severity scoring, and initial triage reducing triage time by around 40%.
  • • Built an end-to-end SSL/TLS Certificate Renewal Agent via Reinvention Agent Manager & CUI to automate lifecycle rotations.
  • 📊 LLMOps, AI Governance & Observability:
  • • Designed full-stack AI governance & monitoring pipelines: live distributed tracing, health dashboards, latency metrics, and logging for enterprise agents.
  • • Implemented AIOps alert intelligence (fingerprinting, deduplication, anomaly detection, and automated RCA) to eliminate alert fatigue.
  • • Unified monitoring across Dynatrace and Datadog into centralized operational views.
  • • Engineered resilient Python microservices optimized with caching and API rate limiting.
  • ☁️ DevOps & Cloud Infrastructure:
  • • Orchestrated automated CI/CD pipelines via GitHub Actions and Azure Pipelines targeting AWS EKS / ECS.
  • • Managed containerized environments (Docker/Kubernetes), incident response, zero-downtime releases, and cross-functional production support.
  • 🛠 Tech Stack:
  • Agentic AI • AWS Bedrock (Claude) • LLMOps • Kubernetes (EKS/ECS) • Docker • Python • Dynatrace • Datadog • AIOps • GitHub Actions • CI/CD

DevOps Engineer

Birlasoft

Sept 2021 to Jan 2025
  • Worked as a Support DevOps Engineer focused on CI/CD automation, cloud infrastructure, and containerization within a microservices environment.
  • 🔹 Built and managed CI/CD pipelines using Jenkins, reducing deployment times by 30% and increasing integration frequency by 20%
  • 🔹 Designed AWS infrastructure using Terraform (IaC) VPCs, Load Balancers, and Target Groups improving deployment consistency by 25%
  • 🔹 Deployed and managed Docker containers within a microservices architecture, improving scalability and fault tolerance
  • 🔹 Gained hands-on experience with Kubernetes for container orchestration, supporting deployment and basic management of workloads in a cluster environment
  • 🔹 Integrated automated vulnerability scanning into pipelines for early security detection
  • 🔹 Set up monitoring and observability using Prometheus and Grafana, ensuring proactive issue detection
Education

BE

DYP pune · 8.89

Apr 2018 to Oct 2021
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