Vetted Batch Processing Professionals

Sahitya Thota

Screened

Staff/Tech Lead Software Engineer specializing in identity, data platforms, and cloud systems

Fremont, CA20y exp

“Engineering leader/player-coach who built and owned end-to-end sales-facing data products, including a 360° advertiser insights platform and a sales AI agent for natural-language access to insights. Demonstrated strong architecture and reliability chops (event-driven redesign to eliminate Hive-query throttling; batching/caching to reduce fan-out) plus incident ownership around ads attribution consistency. Also has 0→1 experience building graph-based recommendation/matching systems with explainability and tight user feedback loops.”

“Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.”

“Built a production LLM-powered data ingestion workflow at Provi, an online alcohol marketplace, to clean and match millions of distributor inventory items against a product catalog. Their experience is strongest in applying LLMs to real-world, large-scale data operations with AWS Glue, S3, batching, API integration, human review, and drift detection.”

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Engineering leader with hands-on product and platform experience spanning AI-powered web forms, multi-region Azure/OpenAI architecture, and full-stack team scaling. They also remain close to production systems, citing a concrete debugging example involving iOS WebView local storage behavior causing token loss in embedded mobile web forms.”

Ahmed Sadaqat

Screened

Senior Machine Learning Engineer specializing in production ML and predictive analytics

Los Angeles, CA7y exp

“ML/AI engineering leader who has owned end-to-end production systems from experimentation through deployment, monitoring, and iteration at meaningful scale. They describe running a 1M+ records/day prediction platform with 99.9% availability, shipping a RAG-based conversational AI feature for 50,000 active users, and consistently improving precision, latency, reliability, and cost with measurable business impact.”

“Fintech and AI product engineer who has owned major production rollouts, including Lending Club's banking-arm launch, and has since built LLM-powered decision systems for finance and climate use cases. Particularly strong in combining stakeholder management with pragmatic architecture choices like observability, deterministic pipeline design, RAG, and document-to-structured-data workflows.”

“Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).”