Vetted Google Cloud Platform Professionals

“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”

“Backend/data engineer with strong AWS production experience spanning serverless APIs and containerized workers (Lambda, API Gateway, ECS) plus data pipelines (Glue, S3, Athena/Redshift). Has modernized legacy SAS/cron batch systems into Python/AWS with parallel-run parity validation and low-risk cutovers, and has owned ETL incidents end-to-end (CloudWatch detection, backfills, and preventative controls). Targeting $130k–$150k base and strongly prefers remote, with occasional Bethesda onsite acceptable.”

“CTO-level leader who drove a major post-buyout transformation at NPact—modernizing engineering (CI/CD, QA, observability), moving products toward SaaS/cloud, and scaling the org from ~20 to ~70 while maintaining 97% retention. Uses instrumentation and workflow analytics (including Atlassian-derived data) to improve delivery, citing an ~80% reduction in feature/bug churn through better scoping and requirements. Comfortable with board-level ROI decisions and customer/fundraising conversations, translating technical tradeoffs into clear business outcomes.”

Chandini Sattineni

Screened

Mid-level Software Engineer specializing in full-stack web, Go microservices, and AI integrations

Remote, USA5y exp

“Backend/LLM engineer who ships production internal tooling end-to-end: automated data-request processing with monitoring-driven improvements (better error diagnostics and lower latency via query/index tuning). Also built a RAG-based internal Q&A system over company docs and operational logs with guardrails (similarity thresholds, fallbacks, response limits) and an eval loop using real user queries and human review to drive prompt/retrieval changes.”

“Repeat founder/CTO with hands-on experience raising capital from friends and family, angels, corporate sources, federal grants, private equity, and venture capital. Built a startup in a software business incubator, later sold the company, and went on to serve as an Engineering Manager at the acquirer inside the Plug and Play accelerator ecosystem.”

“ML/NLP engineer focused on large-scale data linking for e-commerce-style catalogs and customer records, combining transformer embeddings (BERT/Sentence-BERT), NER, and FAISS-based vector search. Has delivered measurable lifts (e.g., +30% matching accuracy, Precision@10 62%→84%) and built production-grade, scalable pipelines in Airflow/PySpark with strong data quality and schema-drift handling.”

“Data engineer with ~4 years of experience building Python-based data ingestion/processing services and real-time streaming pipelines (Kafka/PubSub + Spark Structured Streaming). Has deployed containerized data applications on Kubernetes with GitLab CI/Jenkins pipelines and applied GitOps to cut deployment time ~40% while reducing config drift. Also supported a legacy on-prem data warehouse/backend migration to GCP using phased migration and parallel validation to meet strict reliability/SLA needs.”