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Vetted GitHub Professionals
Pre-screened and vetted.
Abdul Tanimu
Senior Full-Stack Software Engineer specializing in cloud-native web applications
“Backend/data engineer who built a production booking platform on FastAPI microservices (Postgres/Redis/gRPC) and delivered AWS infrastructure spanning Lambda, ECS, SQS, and Glue-to-Redshift analytics. Demonstrated measurable SQL optimization (10 minutes to <40 seconds) and strong operational ownership through monitoring, incident response, and schema-evolution hardening.”
Vaidik Vyas
Mid-Level AI Backend Engineer specializing in Python, LLM/RAG, and healthcare/insurance platforms
“AI Backend Engineer in MetLife’s claims technology group who built and deployed a production LLM-based decision support system that helps claim adjusters quickly find relevant policy rules from long PDFs and historical notes. Designed it as multiple production-grade services with retrieval-first guardrails, continuous validation, and Airflow-orchestrated pipelines for ingestion, embeddings, and vector index updates to keep the system reliable as policies and data evolve.”
Shterna Munitz
Senior Software Engineer specializing in AI/ML and cloud-native microservices
“Backend/platform engineer with production experience building a Python SDK over a microservices ecosystem, emphasizing reliability (JWT auth, retries/timeouts, custom exceptions) and integration testing. Has delivered AWS EKS microservices with Jenkins+Helm CI/CD, strong secrets/config separation using AWS Secrets Manager, and set up Datadog APM/deployment/change monitoring. Also modernized legacy VB applications to C#/.NET WPF via incremental migration with parity testing and stakeholder sign-off.”
sai keerthana peepalpati
Mid-level .NET Backend Developer specializing in secure APIs and enterprise integrations
“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”
Manoj Saddanapu
Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot, React, and cloud
“Backend/platform engineer who built real-time connected-vehicle telemetry analytics at Subaru, spanning Kafka streaming, Python/FastAPI ETL, and low-latency WebSocket delivery (minutes to <2s). Strong Kubernetes + GitOps practitioner across AWS EKS and Azure AKS (Helm, ArgoCD, Jenkins/GitLab) and has led major on-prem-to-cloud migrations for financial microservices using Terraform and AWS DMS with measurable cost and reliability gains.”
KUNAL BABBAR
Mid-level Full-Stack Engineer specializing in AWS serverless and secure web applications
“JavaScript full-stack engineer with experience at EY building secure, cloud-ready React/Node.js applications on AWS and currently at startup Juego Juegos owning the AWS backend and CI/CD via AWS Amplify. Demonstrated impact through performance tuning of a React analytics dashboard (reduced initial load time ~20%) and resolving real payment failures by debugging Stripe 3DS flows and updating AWS Lambda plus frontend error handling.”
Yash Pankhania
Mid-level AI Engineer specializing in LLMs, RAG, and data engineering
“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).”
Krishna Rajput
Mid-level AI Engineer & Data Scientist specializing in LLMs, RAG, and multimodal systems
“LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.”
nitesh bommisetty
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered solutions
“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.”
Indraneel V
Mid-level Cloud & DevOps Engineer specializing in AWS/Azure, Kubernetes, Terraform, and CI/CD
“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.”
Shireesh Kumar Poral Ashok Kumar
Senior Full-Stack Developer specializing in cloud-native web applications
“Full-stack engineer who built an oil & gas analytics dashboard backend using FastAPI, MongoDB, and Redis with a metadata-driven design for dynamic plotting. Shipped an LLM-powered chatbot (LangChain + tool/function calling) to let engineers query analytics in natural language, and also built a multi-step university chatbot workflow with Azure logging, confidence scoring, and human-in-the-loop review.”
Swarnali Biswal
Senior DevOps/Platform Engineer specializing in Kubernetes and cloud infrastructure
“DevOps/Infrastructure engineer with hands-on production experience building Jenkins CI/CD pipelines that provision Kubernetes infrastructure and process data into a MapR cluster. Uses Terraform to provision AWS resources (EC2, S3, VPC, subnets) with remote state in S3, separate environment state files, and code review/validation practices; targeting $135k base.”
Vidit Naik
Junior AI/ML & Full-Stack Engineer specializing in LLMs and RAG systems
“Forward-deployed engineer who built a production AI drone-control chatbot that lets users fly a drone via natural language while viewing a real-time feed. Implemented RAG over drone SDK documentation (vector DB + top-k retrieval) and LoRA fine-tuning, with a focus on latency, token efficiency, and cost reduction, and regularly works with non-technical clients to integrate and explain AI system architecture.”
Filmon Tesfay
Senior Full-Stack Developer specializing in cloud-native FinTech and AI platforms
“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.”
Nicholas Huang
Mid-level Full-Stack Developer specializing in FinTech web applications
“Front-end engineer experienced modernizing legacy React/TypeScript applications, including building a highly customized navigation system controlled by feature flags and documenting it for cross-team adoption. Demonstrates strong performance optimization skills (profiling, provider refactors, memoization) and deep debugging ability, including resolving UI jank traced to Reach Router’s accessibility-driven focus behavior.”
Chandana Arikacherla Nagendran
Mid-level Full-Stack Developer specializing in Java, Spring Boot, and Angular
“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.”
Utkarsh Aman
Senior Frontend Engineer specializing in scalable consumer apps and micro frontends
“Frontend engineer focused on React/TypeScript dashboards for manufacturing-cycle analytics (downtime/wait time/cycle time). Has hands-on experience building reusable charting components (JSON-to-graph) with React ECharts, scaling data flows with Redux/RTK Query, and refactoring monolithic UI code into modular components while shipping on a ~3-week release cadence.”
Mohith Venkata
Mid-level Full-Stack Developer specializing in cloud-native APIs and data workflows
“Built and owned end-to-end ordering and inventory/order management systems for a wholesale distributor, delivering an MVP quickly and iterating based on direct observation of daily users. Experienced with TypeScript/React + Node.js layered architectures and microservices using RabbitMQ, including real-world scaling issues (duplicates, backpressure) and observability practices (correlation IDs, structured logging).”
Hiteksha Godhani
Mid-level Full-Stack Developer specializing in microservices and cloud-native web apps
“Frontend engineer who has led customer-facing web products end-to-end, with strong emphasis on scalable component architecture, design systems, and automated quality gates (CI + unit/integration/E2E). Experienced building complex React+TypeScript dashboards with thoughtful state separation and shipping fast via feature flags/canary releases while monitoring and optimizing real-world performance issues.”
Santhoshi Priya Sunchu
Mid-level Data Scientist specializing in NLP and predictive modeling
“AI/ML practitioner in healthcare/insurance (Blue Cross Blue Shield) who built and deployed a production NLP system to classify patient risk from unstructured clinical notes. Experienced in end-to-end pipeline orchestration (Airflow, AWS Step Functions/Lambda/SageMaker) and real-time optimization (BERT to DistilBERT on AWS GPUs), with strong clinician collaboration to drive adoption.”
Ramya Sree Kanijam
Mid-level Software Engineer specializing in LLM, RAG, and cloud AI
“Recent master’s graduate who led a team project building an LLM-based chatbot with RBAC-controlled information disclosure and a focus on reducing hallucinations. Also has hands-on embedded robotics experience (Arduino obstacle-avoiding robot using ultrasonic sensors) and practical DevOps/cloud deployment exposure with Docker, Terraform, Jenkins, and AWS (EKS/ECS/CodePipeline).”
Ashank Dsouza
Senior Full-Stack Software Engineer specializing in cloud-native web platforms
“Engineer with startup experience who emphasizes disciplined Agile execution (requirements analysis, Jira tasking, sprint planning) and production readiness (testing/QA/PR review). Uses profiling/logging for high-observability debugging and prioritizes incidents by impact. Has demoed engineering processes and worked directly with a client (Canadian music service) to position product capabilities and future extensions to drive adoption.”
Jitesh Kumar S
Junior Machine Learning Engineer specializing in NLP, computer vision, and MLOps
“ML/LLM engineer with Meta experience building production AI systems for near real-time user-report classification and summarization under strict latency (<250ms), safety, cost, and privacy constraints. Has hands-on MLOps/orchestration experience (Airflow, Spark, MLflow, Kubernetes, Docker, GitHub Actions) plus observability (Prometheus/Grafana) and applies rigorous evaluation, staged rollouts, and A/B testing to keep agent workflows reliable in production.”
Butchi Venkatesh Adari
Mid-level Machine Learning Engineer specializing in LLM platforms and robotic perception
“Built and shipped a production multi-agent personal financial assistant at AlphevaAI on AWS ECS, combining FastAPI microservices, Redis/SQS orchestration, and Pinecone-based hybrid RAG (semantic + BM25) to ground financial guidance. Improved routing accuracy with an embedding-based SetFit + logistic regression intent classifier feeding an LLM router, and optimized UX with live streaming plus cost controls via model tiering and caching.”