Vetted Structured Logging Professionals

“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”

“At ReferU.AI, designed and deployed an agentic RAG pipeline that automates multi-jurisdiction legal document drafting, emphasizing hallucination reduction through hybrid retrieval, validation agents, guardrails, and iterative regeneration. Experienced with orchestration frameworks (especially CrewAI) and rigorous testing/evaluation practices including human-in-the-loop review, adversarial testing, and production metrics/logging.”

“Full-stack intern at Rebel who owned backend work on a cross-platform music platform using Python/Django with MongoDB, implementing user-focused REST APIs end-to-end. Also built CI/CD pipelines (Jenkins/GitHub Actions) to containerize and deploy to AWS, and has experience integrating Kafka-based real-time event processing with reliability and observability practices.”

“CloudData engineer who productionized an LLM assistant for a warehouse/logistics customer by wrapping it as a versioned, containerized API with guardrails, deterministic post-processing, and full observability. Experienced diagnosing real-time RAG/agentic incidents (latency spikes and confident-wrong answers) using trace-based isolation, replay in staging, retrieval tuning, and canary releases. Regularly runs technical demos/workshops and partners with sales on security/IAM, SLAs, and pilot rollouts to drive adoption.”

Nagendra Reddy Palugulla

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Florida, United States4y exp

“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”

Jyothsna V

Screened

Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices

USA4y exp

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

Mrudula Devaguptapu

Screened

Mid-Level Software/AI Engineer specializing in backend systems, data pipelines, and RAG automation

United States3y exp

“Backend engineer with experience modernizing high-traffic subscription and payment systems (TCS) by moving to event-driven Spring Boot microservices with Kafka, adding idempotency/state management to eliminate duplicate processing. Built and scaled FastAPI services for AI automation workflows (360DMMC) with versioned contracts, JWT security, and strong observability, and has led live refactors using feature flags, parallel runs, and data reconciliation.”

Yash Amre

Screened

Intern Data Scientist specializing in machine learning and NLP

California, USA1y exp

“Analytics-focused early-career candidate with internship experience owning reporting and system performance analysis projects end to end. They combine SQL data preparation, Python automation, and dashboard delivery with measurable impact, including roughly 50% less manual reporting and about 20% better forecast accuracy.”

“Full-stack product engineer with strong web3/blockchain experience, having built invoicing/tokenization, transaction explorer, and no-code workflow products across React, Node.js/serverless, and SQL. Stands out for combining deep technical execution with product thinking—improving onboarding completion by ~40%, shipping quickly under ambiguity, and creating reusable platform primitives for auditability and multi-tenant customization.”

“Full-stack engineer who built a multi-tenant SaaS analytics dashboard end-to-end with Next.js App Router/TypeScript, emphasizing server components + React Query for performance and real-time UX. Demonstrated strong production ownership post-launch (observability, DB/query tuning, caching strategy) and has concrete wins like 30–40% load-time reduction and Postgres query latency cut to under 200ms.”

“Built and operated AI backend systems at DevFortress and CodeAtlas, including an AI calendar agent used by around 5,000 users and a GitHub repo analysis workflow powered by LLMs. Stands out for owning the full lifecycle of retrieval-based AI products, improving intent detection by ~25%, and bringing a strong reliability mindset through observability, evals, and incident prevention.”

Abhishek Ghaisas

Screened

Intern-level Data Scientist specializing in AI and full-stack applications

Pune, India1y exp

“Engineer with hands-on experience building production ML and Python backend systems, including a real-time social media monitoring pipeline handling 1000+ events per second and a prototype AI operations assistant for Seattle-Tacoma Airport. Stands out for combining reliability engineering, automation, and LLM/NLP-to-SQL work, with measurable impact such as improving uptime from 92% to 99.4%.”

“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”

“Backend Python engineer with end-to-end ownership of secure financial data systems integrating banking/credit/payment platforms, including automated ingestion and reconciliation of large financial statements. Built modular Dockerized Django REST services with pandas-driven validation/normalization and Postgres/Mongo persistence, and supported a phased migration from legacy VM services to AWS containers with stateless refactors and parallel-run integrity checks (run IDs/checksums). Works closely with platform teams on GitOps/CI readiness and deployment coordination (e.g., ArgoCD-managed sync policies).”

“Cloud/distributed-systems engineer who has shipped real-time, offline-capable ledger/expense infrastructure and solved tricky cross-layer production bugs (carrier handoff retries causing duplicate writes) using packet captures and device logs. Also built modular Python ETL/catalog pipelines for e-commerce with config-toggled plugins for customer-specific pricing/SKU rules, and iterated product changes directly with on-site fulfillment operators using feature flags.”

“Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.”

“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”

“JavaScript engineer with open-source experience on a database visualization library, focused on real-time rendering performance for large datasets (virtualized DOM rendering, requestAnimationFrame/debouncing, memoization) and on raising project quality via tests and CI performance benchmarks. Also built Kafka-based messaging documentation and sample producer/consumer apps to speed onboarding, and has experience diagnosing production issues including concurrency-related duplicate data problems.”

Tao Chen

Screened

Senior Full-Stack Engineer specializing in AI-powered web products

Mountain View, CA7y exp

“Backend/data engineer who has built production AI video generation services on AWS using a hybrid serverless + container architecture (FastAPI, Lambda, ECS, Postgres/Redis) with strong reliability practices (auth, retries/timeouts, structured logging, CloudWatch + Slack alerting). Also delivered AWS Glue ETL pipelines with schema evolution handling and modernized a legacy SAS healthcare reporting workflow to Python with parity validation and parallel-run migration.”

Aneri Patel

Screened

Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval

Washington, D.C.2y exp

“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”

Anita Bhagashetti

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud microservices

3y exp

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”

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.”

Jayanth Amol Ergola

Screened

Mid-Level Software Engineer specializing in full-stack development and data engineering

Milpitas, California4y exp

“Backend engineer with production experience at KeyBank building high-volume Java/Spring Boot services on Azure with PostgreSQL/Oracle, including async job ingestion and tracking. Demonstrates strong reliability/performance debugging (HikariCP pool exhaustion, DB contention) and has shipped an LLM-powered data analysis/summarization feature with robust production guardrails (validation, shadow testing, deterministic fallbacks, audit logs).”