Vetted Dashboarding Professionals

“Co-founder at Skarbe who built “Oskar,” an autonomous sales agent that handles inbound email, lead qualification, and automated follow-ups using a multi-agent architecture (OpenAI Agents SDK) with a human-in-the-loop learning phase for reliability. Also owned scaling and reliability of Gmail/Outlook sync, including a Node.js-to-Rails migration and incident response during a Product Hunt launch that generated hundreds of signups and a ~2M-email queue.”

“Data/ML engineer from HCLTech who modernized enterprise data by linking fragmented financial and supply-chain data across SAP/SQL Server/Snowflake using NLP entity linking and embeddings (FAISS). Delivered measurable impact including ~40% reduction in manual error-log triage and entity-linking accuracy improvements from ~86% to ~93%, with results surfaced in Power BI for real-time analytics.”

“Cloud/infrastructure engineer with strong production operations background across AWS, Azure, and Kubernetes, supporting 30+ enterprise workloads for ~40,000 users. Demonstrated incident leadership (hybrid AKS-to-AWS routing outage) with a reported 60% MTTR reduction, plus hands-on CI/CD (Jenkins) and Terraform-based IaC for AWS (VPC/EC2/EKS). Lacks direct IBM Power/AIX/PowerHA experience but emphasizes transferable ops and troubleshooting skills.”

“Full-stack/ML-leaning engineer who has shipped production-grade real-time analytics and an internal AI support assistant using RAG over enterprise documentation. Demonstrates strong systems thinking across scalability, reliability, observability, and LLM safety/evaluation (thresholded retrieval, RBAC, response validation, regression-gated evals), with concrete iteration based on performance metrics and user feedback.”

Sharanya Rao

Screened

Mid-level Backend & Blockchain Engineer specializing in Cosmos SDK and EVM

Remote, USA4y exp

“Built and productionized an LLM+RAG lending assistant on AWS to help loan officers quickly answer questions from credit policies and prior decisions, tackling hallucinations with retrieval-only responses and a no-context fallback. Also automated end-to-end ETL and model retraining/deployment using Apache Airflow, and has experience translating clinical stakeholder needs (doctors/care managers) into ML features, metrics, and dashboards.”

Satish Kumar Reddy

Screened

Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps

Remote, NJ5y exp

“Built and deployed a production LLM/RAG intelligent document understanding platform for healthcare clinical documents (notes, discharge summaries, diagnostic reports), integrating spaCy entity extraction, Pinecone vector search, and a Spring Boot API on AWS with monitoring and guardrails. Demonstrates strong MLOps/orchestration (LangChain, Airflow, Kubeflow/Kubernetes) and a metrics-driven evaluation approach, and partnered with a healthcare operations manager to cut manual review time by 80%.”

Vikram Sandigaru

Screened

Mid-level AI Engineer specializing in AI agents, RAG pipelines, and LLM evaluation

Boston, US3y exp

“Built and shipped production LLM systems at Founderbay, including a low-latency voice agent and a graph-based multi-agent research assistant. Strong focus on reliability in real workflows—hybrid SERP + full-site scraping RAG, grounding guardrails, validation checkpoints, and transcript-driven evaluation—plus performance tuning with async FastAPI, Redis caching, and containerization. Also partnered with a non-technical ops lead to automate post-call follow-ups via call summarization, field extraction, and tool-triggered actions.”

“Built and deployed a full-stack web product for international football fans visiting the U.S. for FIFA, owning everything from crawling and aggregating event data to frontend, backend, deployment, and maintenance. Particularly strong in data-heavy product work, using LLMs, Google Maps API, and SQL/RPC patterns to improve data quality, speed implementation, and support a polished user experience.”

Venkata Sai Niranjan Nadipineni

Screened

Senior Salesforce Developer specializing in Lightning and enterprise CRM

New Jersey, USA8y exp

“Salesforce-focused candidate with hands-on ownership of end-to-end Service Cloud automation, including Apex schedulable jobs for inactive portal user tracking, warning notifications, deactivation, and reporting. Demonstrates strong architectural judgment across Apex, LWC, and Aura, with particular strength in scalable design, performance optimization, and rigorous testing/debugging in complex Salesforce environments.”

“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”

“Built a production Apple-focused LLM Q&A bot that answers user issues using similar past discussion records, including large-scale scraping and cleaning of thousands of forum threads. Used BeautifulSoup + Playwright for static/dynamic extraction, PySpark + NLP for preprocessing, and LangChain RAG with a custom response-likeliness metric to evaluate performance.”

“Built and owned a production RAG search/Q&A platform at Data Integrity First for a client with a large, hard-to-search document library, deployed on AWS. Drove major adoption gains by adding source attribution (users trusted answers more) and improved system performance with guardrails, logging, and iterative chunking/OCR normalization—cutting fallback rate from ~22% to under 10%.”

Pavan Kalyan Reddy Gunamareddy

Screened

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare

TX, USA4y exp

“Backend/platform engineer in fintech/payments (NexaBank/NextBank/Nexon Bank) who has built Kafka-orchestrated Java/Spring Boot microservices around a PostgreSQL double-entry ledger. Led production-critical reliability work preventing duplicate payment postings via idempotency and offset sequencing fixes, and shipped real-time ML fraud scoring (Python model API + Redis caching) with rigorous evaluation/monitoring (Prometheus) and workflow automation for dispute resolution.”

Tanisha Dalwadi

Screened

Mid-Level Full-Stack Product Engineer specializing in TypeScript and React

Arizona, USA4y exp

“Software engineer and co-founder with 0-to-1 SaaS experience who built and owned an end-to-end reporting/analytics dashboard on Next.js App Router + TypeScript, including Postgres schema design, aggregation query optimization, and post-launch performance/monitoring. Has delivered measurable React dashboard performance gains (~35% improvement in time-to-insight) and built durable, idempotent job/state-machine workflows using serverless functions and Postgres.”

Yanet Fernandez

Screened

Junior Data Analyst specializing in healthcare analytics

Fort Myers, FL2y exp

“Analytics/data professional with hands-on experience turning messy semi-structured CRM JSON data in Snowflake into clean reporting layers using SQL and validation logic. Brings a practical mix of data engineering, Python automation, metric design, and stakeholder alignment to improve reporting accuracy and speed of decision-making.”

“Early-career growth/research candidate with hands-on experience using surveys, interviews, Instagram content testing, Excel, and Qualtrics to diagnose conversion friction in a campus dining environment. Stands out for applying structured growth thinking without direct revenue ownership—translating ambiguous problems into actionable recommendations around messaging, convenience, and operating hours.”