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Vetted Alerting Professionals
Pre-screened and vetted.
Executive technology leader specializing in enterprise systems, cloud, and identity strategy
Junior Full-Stack Software Engineer specializing in backend, cloud, and AI systems
Executive engineering leader specializing in SaaS platform architecture
Staff/Lead DevOps & Site Reliability Engineer specializing in cloud infrastructure and Kubernetes
Sangram Jagtap
Mid-Level Full-Stack Software Engineer specializing in web platforms, cloud, and test automation
“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”
Haneesh Kapa
Junior AI Full-Stack Engineer specializing in LLM automations and RAG systems
“Built and shipped a production LLM-powered customer support assistant using a Python/FastAPI backend with RAG (embeddings + vector search) over internal docs and product/operational data. Instrumented the system with logging/metrics and ran continuous eval loops; post-launch improvements focused on retrieval quality (chunking/ranking) and performance/cost tradeoffs (query classification, caching, validation guardrails).”
Bhargav Kommineni
Intern Full-Stack/ML Engineer specializing in cloud-native web apps and LLM systems
“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”
Chinmoy Das
Mid-Level Full-Stack Software Engineer specializing in AI agents and cloud platforms
“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”
Lokeshwar Reddy Gummireddy
Mid-level Backend Engineer specializing in Python APIs, event-driven systems, and Kubernetes
“Backend Python engineer who owned a real-time manufacturing insights streaming service, building FastAPI async microservices with Kafka-style queue buffering, batching/backpressure, and a low-latency snapshot store. Led a serverless-to-Kubernetes (EKS) migration at UGenomeAi using GitOps-style GitHub Actions pipelines, standardized config/secrets, and improved deployment consistency with pinned dependencies and multi-stage Docker builds.”
Sai Vamsee Bandaru
Entry-level Data Analyst and AI Engineer specializing in machine learning and LLM systems
“Founding-engineer-oriented full-stack product engineer who built an AI tutor system end-to-end, spanning React UI, FastAPI backend, retrieval/LLM pipelines, and Postgres optimization. Stands out for combining product thinking with deep systems work: improving onboarding and activation, shipping quickly with beta users, and abstracting reusable retrieval infrastructure for multiple use cases.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native security & compliance platforms
Entry-Level Software Engineer specializing in healthcare data and AI-enabled tools
Mid-Level Backend Software Engineer specializing in PHP/Laravel performance and APIs
Entry-Level DevOps Engineer specializing in CI/CD automation and cloud infrastructure
Mid-Level Software Engineer specializing in distributed microservices and cloud-native systems
Mahaboob Johny
Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards
“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”
Thimone Noupa
Mid-level DevOps Engineer specializing in AWS, Kubernetes, and CI/CD automation
“DevOps/cloud infrastructure engineer focused on AWS automation: built GitHub Actions/Jenkins pipelines for containerized deployments with strong security controls and rollback, and implemented Terraform-based AWS provisioning with modular code and remote state/locking. Has led on-prem to AWS migration cutovers with structured risk/rollback planning and stabilization, but has not worked directly with IBM Power/AIX/LPARs or PowerHA/HACMP.”
Muhammad Murtaza Murtaza
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics
“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”