Vetted Role-Based Access Control (RBAC) Professionals

Thanuja Mudududla

Screened

Mid-level Software Engineer specializing in full-stack cloud and agentic AI systems

San Jose, CA3y exp

“Backend engineer with hands-on ownership of production systems across maritime tracking, HR tech, and AI-powered document workflows. They combine strong operational instincts with measurable impact—cutting API latency from 10s to 3s, improving query performance by 60%, reducing deployment time by 50%, and driving 70% infrastructure cost savings with serverless design.”

“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”

“Backend/data engineer with hands-on production experience building Python (FastAPI/Flask) data enrichment services secured with Okta OAuth2 and monitored via Splunk/Dynatrace. Has delivered AWS event-driven and data-migration solutions (Lambda + Kafka to EKS; Glue from on-prem Oracle to S3/data lake) and modernized Informatica match/merge logic to cloud services using parallel-run parity validation and stakeholder sign-off.”

Naveen Chokkakula

Screened References

Senior Golang Engineer specializing in distributed systems and cloud-native microservices

Texas, USA5y exp

“Software engineer with experience at UWorld and Infosys, focused on full-stack product delivery and backend reliability. Stands out for owning analytics/onboarding experiences end-to-end while also building resilient distributed systems, reusable service primitives, and safe multi-tenant configuration guardrails.”

“Cloud/Linux infrastructure engineer focused on high-availability AWS platforms (EKS/EC2) with strong observability and incident response ownership. Has hands-on experience building secure CI/CD (GitHub Actions/Jenkins) and Terraform-based IaC at scale, including resolving real production issues like peak-traffic latency and Terraform remote state locking; transparent about not having direct IBM Power/AIX/PowerHA production ownership.”

Preet Talati

Screened ReferencesStrong rec.

Junior Full-Stack Developer specializing in .NET Core and React

2y exp

“Full-stack engineer who has shipped end-to-end, customer-facing features in an education/student-population context, including an authorized incident-reporting workflow with RBAC and a PostgreSQL-backed data model. Has 0→1 React+TypeScript/Redux product experience (CTO at Jiffur) and hands-on production operations with CI/CD (Azure Pipelines/GitHub Actions), including resolving a real CPU-saturation outage via operational mitigation and scaling changes.”

“Backend/data engineer who built an enterprise LLM assistant (AI Genie) at Broadband Insights using a LangChain + GPT-4 + Pinecone RAG pipeline to automate broadband analytics reporting. Developed Python/Dagster ETL processing 10M+ records/day and improved data freshness by 60%, with production-grade scalability patterns (async workers, containerized microservices, Kubernetes) and strong multi-tenant isolation practices.”

“Frontend lead on an SME CRM for a bank, building a scalable multi-country/multi-product React/Next.js platform with a config-driven onboarding workflow and multi-role permissions. Emphasizes quality and maintainability through CI gates, a full testing pyramid, and disciplined server-state caching with RTK Query, plus feature-flagged rollouts and data-driven iteration from pilot user feedback.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”