Vetted Confluence Professionals

Sri Vyshnavi Maganti

Screened

Senior Business Analytics Analyst specializing in product and customer analytics

Texas, USA7y exp

“Darwinbox team member who supported talent/recruiting operations while also driving product improvements across HR modules (recruitment, onboarding, payroll, performance). Led a small team (5–6) and implemented discovery-driven configuration and BI reporting (Power BI/Tableau/Confluence), including a reported 30% reduction in recruitment configuration issues and real-time funnel reporting to support fast hiring.”

Somil Shah

Screened

Mid-level AI/ML Engineer specializing in generative AI, RAG platforms, and LLM agents

San Francisco, CA4y exp

“AI/LLM engineer who has shipped 10+ production applications, including InvestIQ on GCP—a production-grade RAG due-diligence engine that ethically scrapes web/PDF sources, builds a ChromaDB knowledge base, and delivers analyst-style dashboards plus a citation-backed chat copilot. Deep focus on reliability (evidence-only answers, hard citations, refusal gating), retrieval tuning, and orchestration (Airflow/Cloud Composer), plus multi-agent systems (CrewAI with 7 specialized finance agents).”

Brian Mar

Screened

Senior Data Engineer specializing in data infrastructure and marketing/CRM analytics

San Mateo, CA8y exp

“Salesforce-focused implementation/solutions engineer from Full Circle Insights who owned end-to-end campaign attribution and reporting deployments for multiple customers at once (3–5 concurrently), including sandbox testing, KPI monitoring, and rollback-safe migrations from legacy reporting. Also builds personal multi-agent workflows and uses Claude Code to rapidly scaffold data/analytics scripts like an advertising optimization parser over CSV/XLSX inputs.”

Aniruth Ravula

Screened

Mid-level Full-Stack Java Developer specializing in Angular and Spring Boot microservices

5y exp

“Full stack Java developer (5 years Java/Spring Boot) building a mortgage-focused rule engine platform used by business users and developers. Experienced scaling data-intensive microservices on AWS (RDS/S3/SQS) and optimizing high-volume rule processing with SQL tuning, caching (KIE container), and asynchronous task decoupling; also delivers modern UIs in Angular and React (Redux/Toolkit).”

Bala Venkateswarlu K

Screened

Mid-level Data Scientist specializing in Generative AI, NLP, and MLOps

USA5y exp

“Built and deployed an LLM-powered claims-document summarization system (insurance domain) that cut agent review time from 4–5 minutes to under 2 minutes and saved 1,200+ hours per quarter. Hands-on across orchestration and production infrastructure (Airflow retraining DAGs, Kubernetes, SageMaker endpoints, FastAPI) and recent RAG workflows using n8n + Pinecone, with a strong focus on reliability, cost, and explainability for non-technical stakeholders.”

“Analytics professional with Northern Trust experience focused on investment portfolio reconciliation and reporting. They combine SQL, Python, and Power BI to clean and validate high-volume financial data, automate manual processes, and align operations and accounting teams on shared metrics—driving roughly 20% improvement in reconciliation accuracy.”

“Worked on a P&C insurance integration project at Accenture, using SQL to unify policy, billing, and claims data from APIs and ETL pipelines into clean reporting tables. Demonstrated hands-on experience with data quality validation, window-function-based transformations, and query performance tuning, helping business teams get a single reliable view for faster claims processing and management reporting.”

“Analytics professional with hands-on experience in supply chain and logistics transformation, including enterprise data preparation in SQL, Python automation, and Power BI reporting. They highlight ownership of end-to-end digitization work at Blue Dart, where they defined operational metrics, aligned cross-functional stakeholders, and delivered measurable gains in transparency, reporting efficiency, and implementation quality.”

“ML/AI engineer with hands-on experience building production systems in financial services, including a real-time underwriting analytics platform at Hartford Financial Services. Stands out for combining classic ML, low-latency API deployment, monitoring, and emerging LLM/RAG design patterns, with measurable impact including 20% better decision accuracy, sub-200ms latency, and 5M+ records processed daily.”

Sarfaraz Karim

Screened

Mid-level Finance Analyst specializing in product, analytics, and technology strategy

Chicago, IL4y exp

“Startup-oriented business development candidate who built outreach and pipeline processes from scratch for early-stage companies including a law firm and consulting-related work. Stands out for highly persistent, research-driven prospecting across social, email, phone, and even in-person outreach, including winning a hotel client after failed remote attempts by showing up with a tailored strategy.”

“Analytics candidate with strong finance/operations reporting experience, focused on billing, margin, and revenue leakage use cases. They have built SQL and Python workflows that turned messy shipment, invoice, PO, and ERP data into trusted reporting layers, replacing manual Excel processes and driving adoption through transparent reconciliation and stakeholder collaboration.”

“Project/program leader focused on large-scale enterprise technology rollouts in highly distributed restaurant environments, including POS, infrastructure hardware, mobile, and SaaS platforms across thousands of locations. Stands out for managing multiple concurrent implementations end to end while coordinating complex cross-functional teams, vendors, governance, and executive stakeholders.”

“Program manager with experience leading a federally oriented biomedical research SaaS platform at Velsera, overseeing contract deliverables, budgets, SOWs, and roughly 10 concurrent projects across cloud-based data and analysis environments. Stands out for managing complex cross-functional initiatives in a regulated research context while maintaining 99.5% budget adherence over two years, plus earlier hands-on biotech operations experience in equipment, sample, and compliance tracking.”

“Frontend engineer with experience building specialized browser-based interfaces for asset management and machine service recommendation systems. Stands out for creating custom UI components like a calendar from scratch in pure JS/TS and CSS, while applying permission-based architecture, design-system constraints, and functional React/Redux patterns.”

Koushik Ravikumar

Screened

Mid-level Full-Stack Engineer specializing in cloud-native Java and AI platforms

Kyle, TX4y exp

“Full-stack engineer with strong cloud and platform experience spanning React, Go, AWS, Kafka, and Terraform. Has led complex migrations from monolithic/containerized systems to microservices and cloud deployments, built compliance-oriented logging infrastructure, and improved a broken frontend codebase to achieve a 3x performance gain while making it easier for other developers to extend.”

Ryan O'Keefe

Screened

Director-level Product Leader specializing in AI-driven SaaS, EdTech, and FinTech

Austin, TX13y exp

“Product leader with 6 years of hiring and management experience who has driven major edtech and mobile product transformations, including a full mobile app rebuild launched in 2 months and an AI-powered content aggregation feature shipped from prototype in 2 weeks. Has worked at OnlineMedEd and Zogo, with a strong track record in personalization, rapid MVP execution, and human-centered AI that supports learning and coaching rather than replacing it.”

“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”

Omkar Tulsidas Parab

Screened

Mid-level Software Engineer specializing in full-stack web and AI applications

United States5y exp

“Software engineer who owned an Order Management System end-to-end at Reliance Jio, improving large-table performance via UI virtualization shipped behind feature flags and refined through direct ops-user observation. Also built an OCR automation tool at Piramal Realty using Python/Tesseract with validation and manual correction fallbacks, driving adoption by operations teams. Experienced integrating with Kafka-based microservices and improving observability using structured logging and correlation IDs.”

Jaisurya Kolluru

Screened

Mid-level Software Engineer specializing in cloud-native backend and AI systems

Virginia, USA5y exp

“Full-stack engineer with hands-on ownership across React/TypeScript frontends, Node.js backends, and PostgreSQL on AWS. Stands out for production-focused database optimization, including execution-plan analysis, indexing, safe migrations, and architectural improvements that reduced database bottlenecks through a centralized REST API layer.”

“LLM/agentic systems practitioner who repeatedly takes customer-facing LLM prototypes into production by operationalizing prompts, hardening RAG pipelines, and adding monitoring/guardrails. Has hands-on experience debugging intermittent production failures under high traffic (vector store timeouts/empty retrieval) and implementing fail-safe behavior plus alerting. Also partners closely with sales in pilots/POCs, customizing demos with customer data and running side-by-side comparisons to drive adoption.”

“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”

“Telecom (Verizon) AI/ML practitioner who built a production multimodal system that ingests messy customer issue reports (calls, chats, emails, screenshots, videos) and turns them into confidence-scored incident summaries with reproducible steps and evidence links. Also built KPI/alarm-to-ticket correlation to rank likely root-cause domains (RAN/Core/Transport), cutting triage from hours to minutes and improving MTTR.”