Vetted Azure Blob Storage Professionals

Teja Babu Mandaloju

Screened

Mid-level Data Scientist/MLOps Engineer specializing in NLP, GenAI, and cloud ML platforms

Chicago, USA5y exp

“AI/ML engineer who led production deployment of a multimodal (text/video/image) RAG system on GCP using Gemini 2.5 + Vertex AI Vector Search, scaling to 10M+ documents with sub-second latency and +40% retrieval accuracy. Strong MLOps/orchestration background (Kubernetes, CI/CD, Airflow, MLflow) with proven impact on reliability (75% fewer incidents) and deployment speed (92% faster), plus experience delivering explainable ML (XGBoost + SHAP + Tableau) to non-technical retail stakeholders.”

Austin Near

Screened

Mid-Level Software Engineer specializing in full-stack and backend systems

Santa Clara, CA3y exp

“Full-stack JavaScript developer in small-company environments building PCB manufacturing web tooling. Owned and delivered blob-storage upload/download infrastructure (including an internal developer library) and a training/compliance tracking tool. Implemented secure, broadly compatible SSO for a customer portal under a <1 month deadline tied to an 8-figure customer deal, despite having no prior authentication experience.”

Aniruddha Chakravarty

Screened

Junior Software Engineer specializing in cloud infrastructure, observability, and full-stack systems

Remote2y exp

“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”

Chin-yu Wu

Screened

Junior Data Analyst specializing in sports analytics and business intelligence

Indianapolis, IN2y exp

“Analytics professional in the sports industry who has owned high-impact revenue and compliance data projects for the Colts, turning fragmented Ticketmaster and Salesforce data into trusted real-time reporting. Stands out for combining strong SQL/Snowflake engineering, rigorous validation practices, and stakeholder-facing metric design that drove a record 98% compliance rate and meaningful revenue recovery.”

Sakshi Patel

Screened

Mid-level Software Engineer specializing in e-commerce and supply chain platforms

Remote, USA3y exp

“AI-focused developer who has built several practical AI products, including EchoMate, a voice-agent system designed to act as a proxy for doctors and support patients when physicians are unavailable. Also has experience with multi-agent/API-based workflows in a solar suitability project, showing interest in applying AI across both healthcare and climate-related use cases.”

“Candidate has hands-on experience using AI-assisted development in a pragmatic, controlled way, including shipping a more user-friendly student feedback form by redesigning text-heavy inputs into checkboxes and dropdowns. They stand out for disciplined review habits: line-by-line validation of AI-generated code, strong edge-case testing, and thoughtful use of structured prompts and staged workflows instead of over-relying on autonomous agent frameworks.”

Rozaliia Russkikh

Screened

Mid-Level Full-Stack Software Engineer specializing in AI systems

5y exp

“Full-stack engineer with hands-on experience leading early AI product initiatives, including a RAG dashboard prototype and a production-ready agentic workflow integrating Front, Airtable, and Slack. Stands out for combining Angular/TypeScript frontend leadership with FastAPI backend work, plus a strong focus on evals, observability, and hardening LLM systems before launch.”

Prabhav Karve

Screened

Junior Software Engineer specializing in data engineering and AI applications

Rochester, NY4y exp

“Data engineer/automation builder with experience at Rochester Regional Health and Accenture, focused on replacing fragile manual reporting with production-grade Azure, Python, and Snowflake pipelines. Stands out for combining strong systems thinking, rigorous validation, and practical AI/LLM usage to drive measurable outcomes, including a 34% throughput improvement and support for regulatory reporting that helped avoid €150M in penalties.”

“LLM/agentic-systems practitioner who has repeatedly taken LLM-driven pricing/decision services from prototype to production using pilots, guardrails, observability, and staged rollouts. Demonstrates strong real-time incident troubleshooting (dependency timeouts, cached fallbacks) and post-incident hardening (isolation/async/alerts), and also supports go-to-market via developer workshops, technical demos, and sales-aligned POCs.”

“Frontend-focused engineer with enterprise Angular experience integrated with .NET APIs, emphasizing production-ready practices (reusable components, modular architecture, TypeScript standards, Jasmine unit tests, and CI/CD). Has not built Unreal Engine UI systems yet, but articulates how they would translate web UI modularity, separation of concerns, and testing/automation practices to Unreal/CommonUI workflows.”

Nidhip Patel

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack development

United States3y exp

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”

Anusha Subbareddy

Screened

Mid-level Embedded Software Engineer specializing in firmware, AUTOSAR, and IoT

Chicago, IL5y exp

“Embedded software engineer with strong end-to-end IoT product experience, spanning STM32/FreeRTOS firmware, MQTT telemetry, Azure IoT Hub integration, and backend data flow for remote monitoring. Particularly compelling for roles at the intersection of devices, cloud, and applied AI, with additional project work in smart parking and TensorFlow-based helmet detection.”

“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.”

“Software engineer with hands-on experience building and maintaining a React accessibility utility/component library (open-source-style) used across university portals, emphasizing WCAG 2.2 compliance, robust focus/keyboard behavior, and Jest/React Testing Library coverage. Also built and maintained .NET Core microservices at the Florida Department of Transportation, including integrating AI-driven features, with strong ownership around observability, incident response, and performance-focused refactoring.”

“LLM/MLOps engineer who has shipped a production RAG-based technical documentation assistant (FastAPI) cutting manual review by 45%, with deep hands-on retrieval optimization in Pinecone/LangChain (HNSW, hybrid + multi-query search, caching). Also brings healthcare domain experience—building Airflow-orchestrated EHR pipelines and delivering FDA-auditability-friendly predictive maintenance solutions using SHAP/LIME explainability surfaced in Power BI.”

“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”

“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.”

“Software engineer with MERN stack experience who says they have built enterprise and SaaS products, set up CI/CD pipelines using GitHub Actions and Jenkins, and created reusable UI components across an application. They also referenced using AI tools like Claude, GPT, Codex, and Cursor with agentic AI concepts, plus CloudWatch-based tracing and crash monitoring.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Backend-leaning full-stack engineer who led a legacy monolith-to-microservices migration (OAuth, Redis, ActiveMQ) while shipping incrementally via CI/CD to avoid user disruption. Strong in search/filter experiences and performance tuning (Solr schema + relevance boosting) with measurable impact (login reduced to ~5s), plus React/TypeScript UI work including configuration-driven filters and shareable URL state.”

“Backend/platform engineer with State Farm experience modernizing and scaling an enterprise consolidated payment data platform and event-driven pipelines. Built cloud-native payment architecture (ECS->EKS) handling millions of financial transactions/day and high-volume telemetry (~100M events/day), with strong schema governance (Avro + schema registry) and production operations/incident mitigation driven by observability.”

Sai Chinthalapudi

Screened

Mid-level Full-Stack .NET Developer specializing in cloud and microservices

United States4y exp

“Software engineer with healthcare platform experience at CVS Health, focused on APIs, SQL performance, and distributed systems. Worked on a 5-6 engineer team building a healthcare simulation platform and drove API/query tuning and caching improvements that cut response times by 50% for real-time, high-volume telemetry workflows.”

“AI/ML engineer (Merkle) with hands-on experience deploying RAG-based LLM applications and real-time recommendation engines into production. Strong in cloud/on-prem architectures, GPU autoscaling, caching, and network optimization—delivered measurable latency reductions (40–70%) and improved retrieval relevance by systematically benchmarking chunking/embedding configurations and validating pipelines via CI/CD.”