Vetted Logging Professionals

“Full-stack engineer specializing in Java Spring Boot microservices and React, with hands-on ownership of a merchant dispute management platform (security via RBAC/JWT, significant performance gains through SQL execution-plan-driven tuning and UI refactors). Also has experience at JPMorgan Chase optimizing high-volume financial-data services with API efficiency, caching, and async processing.”

“At Dreamline AI, built and productionized an AWS-based incentive intelligence platform that uses Llama-2/GPT-4 to extract eligibility rules from unstructured state policy documents into structured JSON, then processes them with Glue/PySpark and serves results via Lambda/SageMaker/API Gateway. Designed state-specific ingestion connectors plus schema validation and automated checks/alerts to handle frequent policy/format changes without breaking the pipeline, and partnered with business/analytics stakeholders to deliver interpretable eligibility decisions via explanations and dashboards.”

“ML/NLP practitioner who built customer-feedback topic modeling (NMF + TF-IDF) to diagnose chatbot-to-agent handovers and drove product/ops changes that reduced operational costs by 20%. Also developed LSTM-based intent recognition using Word2Vec/GloVe embeddings for semantic linking, and deployed an LSTM autoencoder for fraud anomaly detection that cut false positives by 25% while capturing 15% more fraud in A/B testing.”

“Backend/API engineer with ~4 years experience building production services in .NET Core/PostgreSQL/Redis/Docker and optimizing real-world latency issues (claims ~60% response-time improvement). Also built and owned an end-to-end RAG-based AI assistant using Python/FastAPI, OpenAI APIs, and Pinecone, plus agentic workflows with reliability guardrails (retries, confidence thresholds, monitoring). Currently pursuing a master’s degree and targeting a $150k base salary.”

“Data engineer focused on production-grade pipelines and data services: ingests millions of records/day into S3, performs SQL/Python quality validation and PySpark/SQL transformations, and serves curated datasets via Athena/Redshift. Has experience hardening external data collection with retries/rate-limit handling and shipping versioned internal data APIs with backward compatibility, monitoring, and CI/CD in early-stage environments.”

“Data/ML platform engineer with healthcare (Cigna) experience owning an end-to-end pipeline spanning Airflow + Debezium CDC ingestion, PySpark/SQL transformations, rigorous data quality gates, and feature-store/API serving for ML training and inference. Worked at 10+ TB scale and cites a ~30% latency reduction plus stronger reliability via idempotent design, monitoring, and backfill-safe reprocessing; also built pragmatic early-stage data pipelines at Frankenbuild Ventures.”

“Data engineer/platform builder who has owned production pipelines end-to-end processing millions of records/day, with strong emphasis on data quality (quarantine workflows) and reliability (monitoring, retries, incremental loads). Also designed large-scale external data collection/crawling with anti-bot handling and backfills, and shipped versioned REST data services optimized for performance and developer usability in an early-stage environment.”

Ganesh Medepalli

Screened

Mid-level Java Developer specializing in Spring Boot microservices and AWS

USA3y exp

“Backend engineer with primary experience in Java/Spring Boot microservices, AWS (EC2/ECS/Lambda), and CI/CD automation with Jenkins. Supported modernization/migration efforts at Berkshire Hathaway and Citius Infotech by containerizing legacy components with Docker, refactoring services to be stateless, and managing infra changes via Terraform and Git-based workflows; has limited but practical Python API prototyping experience (Flask/FastAPI) and solid conceptual grounding in Kubernetes and Kafka.”

Saicharitha Yanamandala

Screened

Mid-Level Software Developer specializing in Java, Cloud, and Microservices

Chicago, IL6y exp

“Backend/Python engineer who owned an end-to-end FastAPI + AWS internal natural-language document Q&A system (Textract extraction, embeddings/vector DB, LLM integration) with strong focus on reliability and latency. Hands-on with Kubernetes + GitOps (Argo CD, Helm, rolling updates/auto-rollback) and built/optimized Kafka streaming pipelines using Prometheus/Grafana. Also supported a zero-downtime on-prem to cloud migration with parallel run and gradual traffic cutover.”

Kiran M

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data platforms

Bentonville, AR5y exp

“Backend/ML integration engineer with experience at Accenture and Walmart building Flask-based analytics and prediction APIs on PostgreSQL/MySQL. Strong focus on performance and scalability—uses precomputed aggregates, Redis caching, query tuning (indexes/partitioning/EXPLAIN), and async/background processing; also designs secure multi-tenant isolation with JWT and schema/db-per-tenant strategies.”

“Backend engineer with healthcare and financial services experience (Humana, PNC) who owned production-grade, high-volume ingestion-to-API pipelines end-to-end in C#/.NET and SQL. Strong focus on data quality, handling out-of-order/partial upstream records, and improving reliability/observability via structured logging and telemetry, plus significant SQL performance tuning to reduce peak-load issues.”

Krishnamraju Penumatsa

Screened

Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines

Fort Worth, TX6y exp

“Data engineer currently at American Airlines who built and owned end-to-end flight operations and booking data pipelines (batch + real-time) using Azure Data Factory, Kafka, Spark/Databricks, Synapse, and Snowflake—processing hundreds of GBs/day. Strong focus on reliability and data quality (idempotency, checkpointing, retries, validation/alerts) and delivered near-real-time analytics powering Power BI dashboards; previously helped stand up an early-stage data platform at Sysco on AWS (Glue/S3/Redshift) with Airflow and Jenkins CI/CD.”

“Built and deployed an agentic RAG assistant in production to automate enterprise knowledge search and multi-step workflows with tool calling, tackling real-world issues like hallucinations, retrieval accuracy, and latency. Demonstrates strong LLMOps and orchestration depth (MLflow, Airflow, LangGraph/LangChain/LlamaIndex) plus a metrics-driven approach to agent testing/evaluation and cross-functional delivery with business stakeholders.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”

“Candidate approaches AI-assisted coding like a senior developer supervising junior contributors: they define precise technical requirements, enforce code quality and documentation, and review outputs before approval. They also actively lead multi-agent workflows using OpenClaw and a Kanban-style AI project management setup, coordinating both coding and non-technical agents.”

VINAY KUMAR VIPPALA

Screened

Mid-level Software Engineer specializing in FinTech backend systems

Seattle, WA5y exp

“Full-stack product engineer with hands-on ownership from React UI through Spring Boot APIs and SQL data layers, focused on transaction-heavy fintech workflows. Built both a transaction reconciliation system and a 0-to-1 AI-based anomaly detection workflow at LeisurePay, combining performance-minded frontend engineering with pragmatic product delivery.”

“Backend engineer with hands-on ownership of Spring Boot microservice deployments in Freddie Mac's mortgage workflow domain, including measurable gains in reliability and MTTR. Brings strong production debugging skills around distributed transaction pipelines and has also built a full-stack AI chatbot project using React, Express, and Google Gemini API.”

“Engineering leader with 8+ years across IoT, emergency messaging, and political campaign data science, including operating a massive IoT microservices platform at several million devices and roughly 200 million requests per minute. Particularly strong in retrofitting legacy systems for modern observability using OpenTelemetry, Honeycomb, and Grafana LGTM, while also managing distributed international teams and developing engineers into senior and tech lead roles.”

“Full-stack engineer focused on fintech risk and fraud products, with hands-on experience building React/TypeScript dashboards and Spring Boot microservices backed by PostgreSQL, Redis, and AWS. Has also contributed to AI-driven fraud detection workflows using AWS Bedrock, with a strong emphasis on production reliability, analyst usability, and measurable quality metrics.”

“Growth-stage startup engineer with strong end-to-end ownership across React, Java/Spring Boot, MySQL, and cloud deployment. They led workflow automation products that replaced manual operational processes, improved efficiency and reliability, and evolved the platform into a more configurable B2B workflow system shaped by user feedback.”

Rishabh Goyal

Screened

Mid-level Software Engineer specializing in backend microservices and FinTech

USA4y exp

“Python backend engineer focused on real-time e-commerce analytics systems, building FastAPI + Kafka microservices with strong idempotent processing patterns (Postgres upserts, manual offsets, Redis caching). Has hands-on Kubernetes (EKS) and GitOps delivery with Argo CD/GitHub Actions, plus experience migrating containerized services from on-prem VMs to AWS using Terraform and blue-green cutovers.”

Chuangyu Xu

Screened

Entry-Level Software Engineer specializing in Java backend and distributed systems

New York, NY

“Built and shipped a production AI mock-interview platform where an LLM “interviewer” generates role-specific questions, runs multi-turn follow-ups, and outputs structured scoring/feedback using RAG. Demonstrates strong production-readiness practices (Prometheus/Grafana monitoring, retries/timeouts, fallback models/templates, schema validation, replay-based debugging) and achieved 99%+ availability with ~40% higher session completion. Also has experience integrating agents with messy SAP/ERP-style data sources using a data middleware layer, cleaning/validation, and idempotent write safeguards.”

“Backend/data engineer with hands-on production experience building reliable Python FastAPI services on Kubernetes and delivering AWS EKS + Terraform CI/CD with strong secrets isolation and rollback practices. Also built AWS Glue ETL pipelines into S3/Redshift with schema-evolution handling and data-quality controls, modernized legacy analytics into modular Python services with parallel-run parity validation, and has demonstrated SQL tuning impact (minutes to seconds) plus ownership of batch pipeline incidents end-to-end.”