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Vetted Indexing Professionals
Pre-screened and vetted.
Jessy Kattupalli
Mid-Level Full-Stack Java Developer specializing in enterprise web applications
“Backend engineer who built and scaled a transaction-processing microservice (150K+ records/day) in a microservices ecosystem, debugging peak-load latency/timeouts via CloudWatch/Grafana, Kafka lag analysis, and DB query tuning (indexes, Redis caching, batching). Also shipped an LLM-powered document assistant end-to-end with prompt/response validation plus retries/fallbacks for production reliability.”
Dinesh Guguloth
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and GenAI
“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”
Veena Vyshnavi Garre
Senior Full-Stack Software Engineer specializing in cloud-native systems and AI/ML
“Backend engineer who significantly evolved an internal Resource Manager platform, moving from a monolith to microservices and improving onboarding speed while reducing integration errors. Has hands-on experience building reliable and secure Python/FastAPI APIs (Pydantic schemas, circuit breakers, caching, metrics/alerts) and leading zero-downtime migrations with strong data integrity patterns (dual writes, idempotency, reconciliation checks).”
Alankrit Srivastava
Intern Data Engineer specializing in Snowflake pipelines and AI/ML analytics
“Built and operated an end-to-end TypeScript/Node AI agent platform for high-volume financial data that generates explainable investment signals and automates execution via resilient Playwright browser automation. Uses Postgres + pgvector/Prisma for RAG retrieval, Redis for async orchestration, Zod-based boundary validation as a circuit breaker, and OpenTelemetry for tracing/latency monitoring; also designed a TypeScript SDK with semver, scoped bearer-token auth, CLI key rotation, and interactive Swagger docs.”
Sai sri mylavarapu
Junior Data Analyst specializing in BI, ETL, and reporting
“Analytics professional with hands-on experience building SQL and Python workflows across SAP, Oracle, and internal operational systems, processing roughly 5 million records per month. They combine strong data quality rigor with stakeholder-friendly Power BI reporting, and cite a concrete impact of cutting reporting turnaround time from four days to two while surfacing cost anomalies for business teams.”
Nidhip Patel
Mid-level Software Engineer specializing in AI/ML and full-stack development
“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”
Srilalitha Nanjangud Subbaswamy
Junior Software Engineer specializing in cloud-native backend and AI systems
“Early-career software engineer with experience at Cognizant and hands-on ownership of both enterprise backend systems and production LLM workflows. Built an internal certificate monitoring platform to reduce outage risk, and separately shipped a personalized news summarization/recommendation system that cut reading time by 60% and improved CTR@10 by 22%.”
Shterna Munitz
Senior Software Engineer specializing in AI/ML and cloud-native microservices
“Backend/platform engineer with production experience building a Python SDK over a microservices ecosystem, emphasizing reliability (JWT auth, retries/timeouts, custom exceptions) and integration testing. Has delivered AWS EKS microservices with Jenkins+Helm CI/CD, strong secrets/config separation using AWS Secrets Manager, and set up Datadog APM/deployment/change monitoring. Also modernized legacy VB applications to C#/.NET WPF via incremental migration with parity testing and stakeholder sign-off.”
sai keerthana peepalpati
Mid-level .NET Backend Developer specializing in secure APIs and enterprise integrations
“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”
“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”
Abhinay Mangasamudram
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
“Backend engineer with cloud-native Python/Flask experience building high-throughput financial platforms (loan origination intelligent document processing and real-time fraud detection). Has scaled microservices on AKS with event-driven Azure messaging, delivered measurable performance gains (e.g., 700ms→180ms query latency; ~40% API improvements), and implemented strong security controls (OAuth2/JWT, Azure AD RBAC, audit logging, AES-256/TLS) for sensitive regulated data.”
ManiKumar Chintha
Mid-level Full-Stack Java Developer specializing in microservices and cloud (AWS/Azure)
“Backend/full-stack Java engineer at PNC Bank specializing in real-time fraud detection systems. Built event-driven Spring Boot + Kafka microservices with PostgreSQL/Redis performance tuning, and shipped a production LLM-powered RAG feature for fraud analysts with strong guardrails (grounded internal data, structured prompts with references, human-in-the-loop) plus an evaluation loop using labeled historical fraud cases.”
Vidit Naik
Junior AI/ML & Full-Stack Engineer specializing in LLMs and RAG systems
“Forward-deployed engineer who built a production AI drone-control chatbot that lets users fly a drone via natural language while viewing a real-time feed. Implemented RAG over drone SDK documentation (vector DB + top-k retrieval) and LoRA fine-tuning, with a focus on latency, token efficiency, and cost reduction, and regularly works with non-technical clients to integrate and explain AI system architecture.”
Hiteksha Godhani
Mid-level Full-Stack Developer specializing in microservices and cloud-native web apps
“Frontend engineer who has led customer-facing web products end-to-end, with strong emphasis on scalable component architecture, design systems, and automated quality gates (CI + unit/integration/E2E). Experienced building complex React+TypeScript dashboards with thoughtful state separation and shipping fast via feature flags/canary releases while monitoring and optimizing real-world performance issues.”
Utkarsh Aman
Senior Frontend Engineer specializing in scalable consumer apps and micro frontends
“Frontend engineer focused on React/TypeScript dashboards for manufacturing-cycle analytics (downtime/wait time/cycle time). Has hands-on experience building reusable charting components (JSON-to-graph) with React ECharts, scaling data flows with Redux/RTK Query, and refactoring monolithic UI code into modular components while shipping on a ~3-week release cadence.”
Harika Reddymalle
Mid-Level Full-Stack Software Engineer specializing in backend automation and insurance systems
“Full-stack engineer with hands-on production ownership across Angular/.NET/SQL and React+TypeScript/Node/Postgres stacks, including CI/CD and AWS operations (EC2/ECS, RDS, S3, CloudWatch). Delivered an internal insurance document upload and tracking feature end-to-end, adding audit/history and async processing, then validated success through monitoring metrics and reduced support tickets. Comfortable shipping MVPs in ambiguous environments using feature flags, strong validation, and backward-compatible database migrations.”
Shabari Vignesh
Mid-level Data Engineer specializing in cloud data platforms and AI agents
“Data/Backend engineer who has owned end-to-end merchant analytics systems on AWS: orchestrated multi-source ingestion (FISERV/Shopify/Clover) with Step Functions/Lambda, enforced strong data quality gates, and served curated datasets via Redshift and a FastAPI layer. Also built an early-stage Merchant Insights AI agent that converts natural language questions into SQL using OpenAI models, with full CI/CD and observability.”
Tejasri Alla
Mid-level Full-Stack Python Developer specializing in banking microservices
“Built and led production LLM-agent systems in enterprise environments (Simmons Bank, Mindtree), automating support ticket triage end-to-end with strong reliability engineering (99.9% uptime, Prometheus/Grafana, ECS autoscaling, CI/CD rollback). Demonstrated clear business impact (55% faster handling, SLA compliance 72%→96%, 800+ hours saved/month, +18% CSAT) and mature eval/feedback loops that improved extraction accuracy by 21%.”
Dharani Rasaputhra
Mid-level Data Analyst specializing in FinTech and e-commerce analytics
“Analytics professional with experience spanning financial services and e-commerce, including NAV reconciliation/reporting at State Street and revenue optimization work on checkout and retention. Stands out for combining strong SQL/Python data engineering with business-facing analytics, delivering measurable gains like 3-5% conversion improvement and 8-10% payment success uplift.”
Niramay Kelkar
Mid-level Backend Engineer specializing in APIs, microservices, and data platforms
“Software engineer who built JobIntel, an end-to-end Python ETL pipeline integrating ATS data from platforms like Greenhouse using Scrapy and FastAPI. Stands out for production reliability work: designing async fault-tolerant architecture, optimizing PostgreSQL write-heavy upserts, and building a Prometheus/Splunk observability stack that cut debugging from hours to minutes.”
Ishika Khokhani
Mid-level Software Engineer specializing in AI systems and distributed platforms
“Built OpenGPU features spanning React/TypeScript, Go orchestration, PostgreSQL, Redis, and Stripe, with a strong focus on reliability, transaction integrity, and low-latency distributed systems. Also shipped LLM product infrastructure, including persona-conditioned frameworks and reusable prompt/model abstractions, showing a blend of systems engineering and fast product iteration.”
Eoin McDonnell
Staff Python Backend Engineer specializing in cloud-native APIs and microservices
“Backend/data engineer focused on production Python and AWS: built FastAPI REST services and a containerized ECS Fargate + Lambda architecture deployed via Terraform/CI-CD. Strong in data engineering (Glue/S3/Parquet/RDS) and operational reliability (CloudWatch/SNS, retries, schema-evolution handling), with experience modernizing legacy SAS reporting into Python microservices using feature flags and parity validation.”
santhosh ravula
Mid-level Full-Stack Software Engineer specializing in cloud-deployed web apps and APIs
“Software engineer who has shipped both core web platform features (secure user authentication/profile management) and production LLM systems. Built an internal documentation knowledge assistant using a full RAG pipeline (OpenAI embeddings, vector DB, semantic search, reranking) with evaluation loops and a scalable document-ingestion pipeline for PDFs/FAQs, iterating based on metrics and user feedback.”
Hansitha P
Mid-level Data Engineer specializing in scalable ETL/ELT and real-time streaming pipelines
“Built and shipped a production LLM-powered customer support agent for an EV charging platform using RAG plus internal APIs, automating session/payment issues and ticket routing. Emphasizes production readiness via guardrails, schema validation, state-machine orchestration, monitoring, and continuous evals, delivering a reported 35–40% reduction in support tickets and improved customer satisfaction.”