Vetted Observability Professionals

“Backend-focused engineer who built Codesdev V1.0 end-to-end, a cloud-native IDE with secure Docker-based code execution across 8 languages and a custom PostgreSQL JSONB virtual file system achieving 34ms retrieval. Stands out for pragmatic early-stage decision-making, hands-on ownership from architecture through incident resolution, and a strong focus on security and low-latency backend design.”

“Backend engineer (Encore) who led the evaluation and redesign of a high-volume, low-latency real-time retrieval/ranking and inference platform on AWS, shifting from tightly coupled services to a modular architecture for better fault isolation and independent scaling. Strong focus on production reliability, observability, and security (JWT/RBAC, multi-tenant scoping, Postgres/Supabase RLS), with disciplined migration playbooks (feature flags, shadow traffic, dual writes/reconciliation).”

“Backend engineer who has led redesigns and migrations for a real-time logistics platform, improving scalability and resilience while managing eventual consistency tradeoffs. Demonstrates strong distributed-systems rigor (idempotency, transactions, async queues, monitoring) and builds secure, versioned FastAPI APIs with JWT/OAuth2, RBAC, and database row-level security.”

“Built a production multi-agent RAG assistant using LangChain/LangGraph with OpenAI embeddings and FAISS, focusing on retrieval quality and latency (Redis caching, parallel retrieval, precomputed embeddings). Experienced orchestrating ETL/ML pipelines with Airflow and Databricks Workflows, and has delivered an AI assistant for business ops to extract insights from policy/compliance documents through close non-technical stakeholder collaboration.”

“Product-minded full-stack engineer with hospitality tech experience who owned and scaled a multi-region guest verification/check-in workflow (ID/passport scanning, OCR, and government submissions) and built internal tools that cut manual entry up to 80%. Also built a React/TypeScript + FastAPI RAG “second brain” with async ingestion workers and an event-driven e-folio email microservice hardened with idempotency and retries.”

“Full-stack engineer with hands-on experience building end-to-end applications using Java/Spring Boot and React, including Dockerized deployment and RabbitMQ-based messaging. Worked on a high-volume payment processing system at Alacriti, focusing on performance (query optimization, caching) and reliability with monitoring via AWS CloudWatch.”

“Frontend-leaning engineer who shipped an end-to-end map-based discovery feature in a React Native mobile app, integrating location-based REST APIs with strong UX polish (loading/empty/error states) and cross-platform performance fixes. Also has experience building a Python backend with JWT auth and layered service structure, plus prior infrastructure work setting up centralized logging and monitoring.”

“Built and productionized an AI-assisted merchant onboarding automation workflow for Kort Payments, replacing slow manual underwriting document review with structured extraction, cross-document validation, and human-in-the-loop guardrails. Emphasizes reliability via scenario-based testing, repeatability checks, and deep observability (timestamped logs), plus incremental rollout with legacy fallback to prevent regressions.”

“Built and shipped production LLM agents for real-time, high-concurrency conversational systems, including a RAG-based pipeline with dynamic multi-provider routing and failover that achieved 99.99% reliability and sub-800ms latency. Also architected a UAV telemetry chatbot with tool-calling (anomaly detection/summarization), strict schema validation, and robust eval/monitoring loops, cutting tool-call errors by 30% and reducing operational costs by 90%.”

Ahmad Alomari

Screened

Senior Data Scientist & Machine Learning Engineer specializing in computer vision and production ML

Cleveland, OH7y exp

“PhD in computer engineering who has built production-oriented ML/NLP systems for space-weather prediction using Spark-based ETL on noisy satellite sensor logs. Strong in entity resolution and semantic search—fine-tuned E5 embeddings with contrastive learning and deployed to Pinecone, improving top-5 retrieval precision by 25%—and emphasizes scalable, observable pipelines with Airflow, Docker, and CI/CD.”

Ramya Jonnala

Screened

Principal/GenAI Engineer specializing in LLMs, RAG, and MLOps

Plano, TX9y exp

“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”

Riya Stanly

Screened

Intern Data Scientist specializing in machine learning, NLP, and LLM fine-tuning

2y exp

“Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).”

Swapnil Sanjay Pawar

Screened

Junior Full-Stack Software Engineer specializing in GenAI and web platforms

Atlanta, GA2y exp

“AI/software engineer with hands-on experience deploying an LLM-powered quiz generation platform for students, integrating Python services with Gemini APIs plus frontend and database components. Emphasizes production-grade reliability through observability, schema validation, async processing, and performance tuning under high concurrency, and has collaborated with product/operators (e.g., at Colombo AI) to translate real-world constraints into scalable technical solutions.”

Tim Kwok

Screened

Senior DevOps Engineer specializing in multi-region AWS/GCP cloud infrastructure

United States8y exp

“Backend/data engineer with strong AWS production experience spanning FastAPI microservices and large-scale data pipelines. Has delivered containerized Python services on EKS with Terraform/Helm/GitHub Actions, implemented robust auth/secrets practices, and owned ETL reliability (Glue/S3/Redshift) including incident response and idempotent reruns. Demonstrated SQL tuning on 50M-record ETL workloads to remove SLA misses and improve reliability.”

Asad Abdul

Screened

Mid-level Full-Stack Developer specializing in AI-driven cloud-native applications

Laguna Niguel, CA4y exp

“Full-stack engineer with healthcare/ops analytics experience at PatientXpress, shipping a real-time operational dashboard end-to-end (React/TypeScript + Node/Postgres on AWS) that cut manual reporting by 50%. Strong in performance and reliability work—pagination/caching, Postgres indexing/partitioning, Terraform-based AWS provisioning, CI/CD with GitHub Actions, and production incident response with improved monitoring (CloudWatch/Prometheus).”

ROHITH DAMARLA

Screened

Mid-level Backend Engineer specializing in high-scale systems and LLM pipelines

Syracuse, NY6y exp

“Open-source-focused TypeScript/JavaScript engineer who built a lightweight Node.js utility library to standardize LLM-agent message formatting, tool invocation, and safe schema-validated JSON outputs. Emphasizes composable abstractions, real-world performance profiling/benchmarks, and strong community feedback loops (GitHub issues, structured errors, logging hooks). Also did research at Syracuse University on converting natural language into structured JSON with validation layers.”

Charmi Dharmendrakumar Parmar

Screened

Mid-Level Software Engineer specializing in full-stack and cloud-native systems

Alpharetta, GA4y exp

“Backend/full-stack engineer who owned a cloud-native, AWS-based microservices backend for an HRIS product used by ~10,000 users, including onboarding and workflow orchestration. Strong production focus on event-driven architecture, idempotency/retries, observability, and developer-friendly API design (OpenAPI, versioning, JWT), plus hands-on Selenium automation for resilient checkout-style flows.”

“AI/ML engineer with hands-on experience owning production deployments from discovery through post-launch stabilization, including real-time computer vision/OCR systems and LLM-powered RAG workflows. Stands out for translating messy customer workflows into reliable backend services, debugging non-deterministic retrieval issues, and hardening AI systems with validation, monitoring, and human-review fallbacks.”

Emma Choudhary

Screened

Senior Full-Stack Software Engineer specializing in Python, Django, and Generative AI

United States6y exp

“Backend/data engineer with hands-on production experience building partner-facing Python APIs (FastAPI, Celery, Postgres/Redis) and AWS serverless data platforms (Lambda, SQS, Step Functions, Glue). Emphasizes reliability and governance—JWT tenant-scoped auth, secrets/config hygiene, data-quality quarantine, and incident ownership—plus measurable SQL tuning that eliminated timeouts and stabilized reporting workloads.”

“Infrastructure engineer focused on AWS platform automation: built a full CloudFormation-based environment (networking, Aurora, ElastiCache) and created Python tooling plus Lambda-backed custom resources to automate deployments, user provisioning (MySQL/RabbitMQ), and operational workflows. Also migrated a company from Rackspace to AWS and maintains an 8-year Debian homelab with VMs/containers, RAID6 backups, and GPU passthrough troubleshooting. No Kubernetes experience.”