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Sairam Bodapothula
Mid-level AI/LLM Engineer specializing in generative AI and ML systems
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AI/LLM-focused engineer with hands-on experience building RAG pipelines, prompt engineering workflows, and multi-agent systems using tools like LangChain. Stands out for combining AI-assisted development with production-grade validation and for leading the architecture/orchestration of agent-based recommendation systems that improved response time, accuracy, and scalability.
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Key Strengths
- Hands-on experience building RAG and LLM-based systems
- Practical use of multi-agent architectures for AI workflows
- Balances AI-assisted coding with rigorous validation and production standards
- Designed agent orchestration, context sharing, and validation flows
- Improved response time, accuracy, and scalability in a RAG recommendation system
- Strong experimentation mindset with emerging AI models and frameworks
- Owned end-to-end backend delivery (API design, Postgres schema, Redis caching, auth/logging, Dockerized AWS deployment)
- Performance optimization improving API response times ~20–25%
- Scaled Celery background processing under heavy load (concurrency tuning, broker optimization, batching)
- Kubernetes production deployments with Helm and robust health checks (readiness/liveness, autoscaling, secrets/configmaps)
- GitOps/ArgoCD automation enabling versioned, rollback-friendly, zero-downtime rollouts
- Resolved ArgoCD/Helm drift issues via immutable image tags and automated tag updates
- Planned/executed on-prem to AWS migration with phased cutover, CDC replication, and ALB traffic shifting
- Built Kafka streaming pipeline and mitigated consumer lag + schema evolution via partition scaling and schema registry
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