Vetted Data Modeling Professionals

Srichandan Kota

Screened

Senior Full-Stack AI Engineer specializing in Generative AI and FinTech

Minneapolis, MN6y exp

“Backend engineer who built and owned an AI-powered financial research product end-to-end, using a typed NestJS/GraphQL backend with LangGraph-style agent routing to produce sourced, structured financial analysis. Emphasizes finance-grade correctness (Zod validation, metric registries, unit/empty-result guardrails) while keeping latency low via batching, caching, and fast token streaming, and has led incremental migrations using strangler/feature-flag/shadow traffic patterns.”

“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.”

“Analytics candidate with hands-on experience improving enterprise reporting and operational decision-making at Reliance and Wendy’s. They combine SQL optimization, Python automation, sentiment analysis, and dashboarding to deliver measurable impact, including cutting report runtimes from 3 minutes to 1 minute, improving model accuracy from 70% to 80%, and reducing supplier past dues by 30%.”

Sairam Prasad

Screened

Mid-level Full-Stack Engineer specializing in AI-powered web platforms

United States4y exp

“Fullstack engineer focused on AI-powered customer-facing products, with hands-on experience building semantic search, document intelligence, and story-analysis platforms from scratch. Stands out for owning architecture and implementation across React/Next.js frontends, GraphQL/FastAPI backends, and async AI pipelines, while also shaping product direction through direct customer feedback in ambiguous startup environments.”

Julian Thong

Screened

Senior Software Engineer specializing in FinTech platforms

San Francisco, CA4y exp

“Senior software engineer with deep experience in private markets platforms, spanning full-stack product development and complex backend modernization. Notably helped migrate a core IOI processing system from a Rails monolith to .NET microservices with Kafka-based event sequencing, and contributed to an Offerings platform that drove 50% faster transactions for investors and operations teams.”

“Lead full-stack engineer with strong Python backend depth and hands-on React/TypeScript experience, working in startup-like B2B SaaS environments serving enterprise software customers such as CrowdStrike, HashiCorp, and VMware. Stands out for redesigning tightly coupled systems into modular AWS-based microservices and building configurable integration platforms that improved enterprise customer onboarding and marketplace workflow scalability.”

“Hands-on AI/LLM practitioner who built a RAG-based customer support chatbot and tackled production issues like data chunking complexity and response-time lag. Uses techniques such as overlapping chunks, semantic search, context engineering, and query routing, and has experience presenting technical demos/workshops to developer audiences.”

“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.”

“AI Engineer Co-Op at Northeastern University who built a production Patient Persona Chat Bot to help nursing students practice clinical interactions, fine-tuning Llama 3 and integrating a LangChain + Pinecone RAG pipeline deployed on Amazon Bedrock. Emphasizes clinical accuracy and reliability with guardrails, retrieval filtering, and continuous evaluation, and also brings strong data engineering/orchestration experience (Airflow, EMR/PySpark, ADF, dbt, Databricks, Snowflake).”

“AI/NLP-focused practitioner who built a zero-/few-shot LLM event extraction system on the long-tail Maven dataset, combining prompt-structured outputs with LoRA/QLoRA fine-tuning and rigorous F1 evaluation. Also implemented entity resolution/data cleaning pipelines and embedding-based semantic search using Sentence-BERT + FAISS, and has healthcare experience delivering a multilingual speech/translation mobile prototype using HIPAA-compliant Azure Cognitive Services.”

“LLM engineer who built a production-style educational questionnaire generation system (MCQs/fill-in-the-blanks/short answers) using Hugging Face models (BERT/T5) and implemented grounding, decoding tuning, and post-generation validation to control hallucinations and quality. Also developed a "tech care" assistant chatbot with a custom Python orchestration/router layer (intent classification, context management, multi-step flows) and a structured testing/evaluation approach including expert review and automated checks.”

“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.”

“IBM Power/AIX infrastructure engineer with hands-on production experience across Power8/Power9 frames, VIOS and HMC, including resolving a production LPAR outage caused by vFC mapping issues. Has operated PowerHA clusters for critical finance workloads, running quarterly failover tests and handling an unplanned failover triggered by a network adapter failure, then improving resilience with redundancy and monitoring automation.”

“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.”

Filmon Tesfay

Screened

Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms

New York, NY8y exp

“Full-stack engineer with strong production ownership: built and operated a real-time transaction monitoring/fraud-alerting system using Java Spring Boot, Kafka, Docker, and AWS with CI/CD. Demonstrates metrics-driven operations (latency, stability, consumer lag, true/false positives) and reliability patterns for integrations (idempotency, retries/backoff, DLQs, reconciliation/backfills), plus modern React/TypeScript + Node/Postgres architecture experience.”

Chandana Arikacherla Nagendran

Screened

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

Columbus, Ohio4y exp

“Full-stack engineer who modernized mission-critical legacy COBOL/AS400 systems into a Java + Angular/TypeScript web application, owning backend APIs, UI, database performance tuning, and JWT security end-to-end. Built and transitioned an internal docketing/hearing scheduling system with complex business rules, emphasizing smooth adoption, performance, and quality through phased agile delivery.”

Shabari Vignesh

Screened

Mid-level Data Engineer specializing in cloud data platforms and AI agents

Santa Clara, CA6y exp

“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

Screened

Mid-level Full-Stack Python Developer specializing in banking microservices

Northridge, CA5y exp

“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%.”

“Founding/early engineer experience across Asante and a Series A startup (Adgency), shifting from data science/ML into owning production full-stack systems end-to-end. Built core product flows (registration, business profiles, map service), AWS-deployed gRPC microservices with CI/CD, and operated low-latency agent/video ad generation workflows with retries/fallbacks and PostHog-based observability.”

“Former Database Marketing Analyst with hands-on SQL experience supporting targeted casino marketing campaigns and a strong emphasis on validation accuracy. Also describes owning analytics work that standardized engagement metrics across teams, automated cohort/segmentation reporting, and helped identify onboarding friction that improved user engagement.”

“Built and deployed an end-to-end fintech product, FinSight, for bank statement analysis and financial Q&A using a production-style RAG architecture. Stands out for combining FastAPI, OpenAI embeddings, FAISS, hybrid SQL/vector retrieval, and practical reliability work like chunking optimization, validation, and low-latency performance tuning.”

“Built end-to-end AI products across fintech and healthcare, including a real-time loan risk prediction system and a patient feedback insights platform. Stands out for combining full-stack delivery, production ML/MLOps on AWS, and pragmatic human-in-the-loop safeguards; reported a 22% improvement in prediction accuracy.”

“Senior hands-on full-stack engineer with recent Python/React/TypeScript experience at Terakeet and prior Go-focused backend work at Checkly. Stands out for building and scaling analytics and monitoring platforms in startup-style environments, with strong depth in PostgreSQL performance, containerized deployments, and turning ambiguous business goals into reliable production systems.”

“Performance marketing specialist with hands-on ownership of $50K+/month spend on the AdOn Network at RhythmOne, focused on driving new-user growth and on-site engagement. Known for rigorous, variable-isolated testing across keywords, placements, and ad copy, plus clear client reporting tied to engagement and efficiency metrics.”