Vetted Azure Functions Professionals

“Backend-focused engineer who built an internal wiki LLM chatbot end-to-end using FastAPI, Kubernetes, and ChromaDB vector search, including frontend integration. Also has strong DevOps/migration experience—automating large work-item and repo migrations (Jira/FogBugz/ADO on-prem to cloud) via Python scripts, JSON mappings, REST APIs, and validation test suites.”

“Data engineer with experience at Moderna and Block owning high-volume (≈10TB/day) production pipelines on AWS, using Kafka/S3/Glue/dbt/Snowflake with strong data quality and observability practices (schema validation, anomaly detection, CloudWatch monitoring). Also built external financial API ingestion with Airflow retries, throttling/token rotation, and schema versioning, and helped stand up an early-stage biomedical data platform with CI/CD and incident debugging.”

Travoy Spelling

Screened

Senior Data Scientist / ML Engineer specializing in GenAI, LLMs, and NLP

Texarkana, TX10y exp

“ML/NLP engineer focused on production GenAI and data linking systems: built a large-scale RAG pipeline over millions of support docs using LangChain/Pinecone and added a LangGraph-based validation layer to cut hallucinations ~40%. Also built scalable PySpark entity resolution (95%+ accuracy) and fine-tuned Sentence-BERT embeddings with contrastive learning for ~30% relevance lift, with strong CI/CD and observability practices (OpenTelemetry, Prometheus/Grafana).”

“Senior data engineer with experience in both healthcare (CVS Health) and financial services (Bank of America), building large-scale Azure lakehouse pipelines (30+ EHR sources, ~5TB) and real-time streaming services (Event Hubs/Kafka) for patient vitals. Strong focus on reliability and data quality (Great Expectations, monitoring/alerting, schema drift automation), with measurable outcomes like 50% runtime reduction and 99%+ uptime for regulatory reporting pipelines.”

Sai Dinesh Pusapati

Screened

Senior AI/ML Engineer specializing in GenAI agents and LLM workflows

San Francisco, CA6y exp

“LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.”

“Backend engineer with hands-on experience building Flask REST APIs (auth, CRUD, S3 media uploads) and driving measurable Postgres/SQLAlchemy performance gains (p95 reduced to 200–400ms by eliminating N+1s and switching to keyset pagination). Implemented multi-tenant isolation with strict tenant scoping plus Postgres RLS, and built an OpenAI-powered quiz generation pipeline using queued workers, structured JSON outputs, and Celery/Redis optimizations to stabilize high-throughput workloads.”

Kunal Singh Pundir

Screened

Mid-level Full-Stack Developer specializing in cloud microservices and GenAI systems

USA, USA5y exp

“Built and owned an end-to-end AI-driven decisioning platform at Uber, combining LLM orchestration with typed tool contracts and a Snowflake-based RAG pipeline to make decisions fully auditable. Delivered large-scale measurable impact (120k requests/day, 18k cases auto-resolved/month) while improving ops SLA from 3 days to 6 hours and cutting incident response time nearly in half. Previously led a high-risk strangler-fig modernization of a legacy insurance platform across 120+ microsites at Accenture, coordinating across multiple squads with feature-flagged parallel cutovers.”