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Vetted Microsoft Azure Professionals
Pre-screened and vetted.
Rohan Varma Bandari
Mid-level Data Scientist & Generative AI Engineer specializing in LLMs and RAG
“Built production LLM + hybrid RAG and multi-agent orchestration systems at Wells Fargo to automate complaint document/audio transcript understanding and categorization, addressing vocabulary drift via embedding + vector index updates instead of frequent retraining. Strong in LLM workflow reliability (testing/benchmarks/observability) and stakeholder-facing delivery with explainability (citations/SHAP-style justifications) and Tableau dashboards.”
Sreeja Venkatakrishnan
Mid-level Full-Stack Developer specializing in Java/Spring and modern JavaScript frameworks
“Full-stack engineer with hands-on experience building real-time applications (Socket.io chat app) and data-heavy systems in banking/loan management. Comfortable across React and backend services (Spring Boot/Node), with a focus on scalable API design, database performance (indexing/pagination/caching), and deployment via CI/CD and cloud infrastructure.”
Siddhartha Alapati
Mid-Level Software Engineer specializing in Java/Spring microservices and full-stack web apps
“Software/full-stack engineer focused on deploying and integrating microservice applications into production AWS and hybrid cloud/on-prem industrial environments. Demonstrated end-to-end troubleshooting by tracing intermittent user failures to network routing/packet loss caused by load balancer and NIC misconfiguration, then adding monitoring to prevent recurrence. Also delivers customer-specific Python extensions with strong validation, testing, and backward compatibility.”
Harideep Balusa
Mid-level AI/ML Engineer specializing in FinTech risk, fraud detection, and GenAI/RAG systems
“Built and productionized Azure-based LLM/RAG systems for regulatory/compliance use cases, including automating analyst research and compliance report generation across large unstructured document sets. Demonstrates strong practical depth in hallucination mitigation, hybrid retrieval tuning (BM25 + embeddings), and production MLOps (Databricks, Cognitive Search, AKS, Airflow/MLflow), plus proven ability to deliver auditable, explainable solutions with non-technical compliance teams.”
Ojasmitha Pedirappagari
Mid-level AI Engineer specializing in LLMs, RAG, and agentic platforms
“Built and shipped a production RAG-based assistant that lets parents ask natural-language questions about their child’s learning progress, using pgvector retrieval (child-id filtered) and Redis caching to hit ~180ms latency. Implemented real-world guardrails and compliance (Llama Guard, COPPA, retrieval thresholds, fallbacks) with 99.5% uptime, and ran human-in-the-loop eval loops that improved satisfaction from 3.8 to 4.2 while serving 60k+ monthly users and reducing costs significantly.”
Srilekha Jakkula
Senior Data Engineer specializing in scalable data pipelines and API-driven data services
“Data engineer focused on building scalable, reliable end-to-end data pipelines and backend REST data services, spanning API ingestion plus batch/stream processing with Airflow, Kafka, Spark/PySpark, and SQL. Emphasizes strong data quality validation, monitoring/fault tolerance, and performance tuning for large datasets, with experience deploying in cloud environments using containerization and CI/CD.”
Gitesh Sagvekar
Mid-level Full-Stack Developer specializing in cloud-native healthcare applications
“Full-stack engineer with recent experience at Amgen building an internal healthcare data validation/transformation and workflow automation service: Python/FastAPI backend with REST APIs plus a React UI, designed around a canonical contract-first model to handle inconsistent upstream data. Operates production systems on AWS (EC2/ELB/S3/CloudFront) with strong focus on observability (structured logs, correlation IDs) and safe CI/CD-driven migrations; also has experience shipping quickly in ambiguous environments at TCS.”
Zubair Shaik
Mid-level Full-Stack Developer specializing in AI-driven FinTech platforms
“Built and productionized an LLM-powered loan decisioning agent at Bank of America, integrating RAG with microservices to automate creditworthiness assessment and recommendations. Emphasizes real-world reliability and governance (EKS autoscaling, observability, SOC2/PCI security controls), and drove measurable outcomes including 20% faster loan decisions and a reduction in agent failures/fallbacks to under 2% through schema enforcement and confidence-based routing.”
SreeHarsha Kelam
Senior DevOps / Site Reliability Engineer specializing in cloud infrastructure
“GCP-focused database/platform engineer with hands-on production experience operating Cloud SQL at scale, especially around performance tuning, reliability, and day-2 operations. Has supported migration from a single-instance database setup to a more scalable GCP architecture and built Terraform/Python automation for provisioning and recovery workflows.”
James Furr
Senior Information Security leader specializing in cloud infrastructure and compliance
Srijitha Katkuri
Mid-level Data Analyst specializing in healthcare and business intelligence
“Healthcare analytics candidate with hands-on experience turning messy EHR, billing, and operational data into validated SQL datasets and automated Python/Airflow pipelines. They appear strongest in hospital KPI reporting—especially length of stay, readmissions, retention, and bed utilization—and have owned projects from metric definition through Power BI delivery and impact measurement.”
Cia Hang
Executive IT and Operations leader specializing in digital transformation and security
“Candidate is very familiar with the venture capital and broader investment landscape, but is not interested in founding a company. They have worked with several TPG-backed or TPG-owned organizations, helping drive business scaling, cost reduction, and execution against investor governance requirements.”
Tara Worrell
Senior Software Engineer specializing in backend systems, AI/LLM integration, and cloud infrastructure
“Backend engineer with experience in highly regulated and high-stakes systems, including an airline crew messaging platform requiring near-zero-error real-time operations and a HIPAA-compliant mental health application built from an early-stage concept. They also show strong operational maturity, having owned a GoDaddy production incident through resolution and then led deployment pipeline improvements that reduced build failures by 40% and doubled deployment frequency.”
John King
Executive technology leader specializing in SaaS product and engineering
“Entrepreneur building an AI-driven outbound growth and automation startup, currently self-funding development through consulting while validating market demand. Stands out for combining technical workflow automation with practical go-to-market experimentation, including deliverability-focused outbound systems and webinar partnerships with local experts to drive trust and conversion.”
Alekya Battu
Mid-level Data Scientist specializing in machine learning, MLOps, and cloud analytics
“Senior data scientist with ~5 years’ experience building production ML/NLP systems in finance (Wells Fargo) and deep learning for sensor analytics in connected vehicles (Medtronic). Has delivered end-to-end platforms combining time-series forecasting with transformer-based NLP, including automated drift monitoring/retraining (MLflow + Airflow) and standardized Docker/CI/CD deployments; achieved a reported 22% precision improvement after domain fine-tuning.”
Adhiraj Chadha
Junior Software Engineer specializing in AI, data, and full-stack applications
“Builder with a mix of backend engineering, product instinct, and startup execution: they shipped a legal BI platform from scratch that handled 1,000+ cases, cut reporting time 80%, and saved $30K annually. They also move quickly in ambiguous environments, from launching a roommate app across iOS/Android after user discovery to building a RAG system with a 50+ case evaluation suite and a cloud dev environment in under 48 hours.”
Parnashri Nandam
Mid-level AI Engineer specializing in LLMs, RAG, and production ML systems
“Backend engineer who built an AI-powered grant matchmaking platform for researchers and professors, combining semantic matching, embeddings, and Semantic Scholar enrichment with rule-based eligibility filters. Stands out for pragmatic AI engineering: they focused on reliability through confidence scoring, logging, manual validation, and production-minded backend design.”
Sachin Bhangale
Senior ERP implementation consultant specializing in manufacturing and supply chain systems
“Functional/implementation consultant with experience across 10+ ERP deployments, including Infor LN and Salesforce/Rootstock, primarily in manufacturing environments. Brings hands-on ownership across the full lifecycle—from requirements, process mapping, configuration, and documentation through UAT, training, go-live, and hypercare—with particular depth in shop floor, procurement, inventory, and global operational complexity such as tax and shipping integrations.”
Eric Okunevich
Executive product leader specializing in SaaS, Industrial IoT, and logistics
“Product leader with experience modernizing and merging complex B2B platforms in industrial, facilities, and logistics contexts. Notably led the integration of Smartbin and WasteForce into a single Contelligent platform with no customer attrition, and has shipped AI-informed IoT products that made building optimization more accessible to non-analytical users.”
AadarshKumar Vanga
Mid-level Full-Stack .NET Developer specializing in healthcare and financial platforms
“Backend/ML systems engineer who built a Flask + PostgreSQL internal ticketing platform and demonstrates strong database/ORM performance depth (indexes, partitioning, RLS multi-tenancy). Notably optimized a high-throughput attachment OCR/embedding pipeline with batching, deduplication, and Redis caching, cutting median latency from 45s to 10s and reducing worker cost by 35% while increasing throughput 4x.”
Hard Parikh
Mid-level Software Engineer specializing in data platforms, distributed systems, and applied AI
“AI/full-stack product engineer currently owning Fleck Intelligent Survey Chatbot at E15, a production RAG analytics assistant embedded in Compass Group dashboards for 300+ field operators. Stands out for combining LLM orchestration, analytics engineering, and strong systems thinking—cutting hallucinated numeric answers from 14% to 2%, reducing backlog 62%, and previously delivering a low-level protocol redesign at Amadeus that cut P99 latency by 56%.”
Manoj Manjunatha
Mid-level Software Engineer specializing in full-stack systems and applied AI
“Built the backend for “codeGuard,” an AI-powered static code analysis platform, using FastAPI and Docker. Structured the system into API/service/execution layers and addressed heavy-workload container resource/cleanup issues via strict CPU/memory limits and a queued execution model.”
Vigneshreddy Kaligota
Mid-level Java/Spring Boot Engineer specializing in microservices and cloud platforms
“Full-stack engineer with deep production experience across healthcare, e-commerce, and financial systems, including early-stage startup architecture work and large-scale enterprise platforms. Stands out for driving a Spring Boot/RabbitMQ microservices migration that stabilized healthcare claims processing and for leading React modernization work supporting 50M+ weekly e-commerce transactions.”
Sid Daniel
Senior Full-Stack Engineer specializing in microservices and cloud platforms
“Backend-focused engineer with strong Go and database optimization experience who improved a high-traffic API by about 30% and helped stabilize peak-load performance for an event reservation platform. Brings hands-on production experience across PostgreSQL, Redis, Rails/Go services, and B2B SaaS integrations with Slack, Hubstaff, and RingCentral, with a clear pattern of owning performance bottlenecks end to end.”