Vetted Docker Professionals

“Built practical automation systems spanning an NLP-based news classification pipeline and a WhatsApp interaction agent. Shows strong instincts around production reliability—using structured outputs, schema validation, idempotency, retries, and clarification flows to prevent bad actions in real-world messaging workflows.”

“AI/LLM engineer who has shipped production RAG copilots and multi-agent workflows, including a real-time Llama3 (Ollama) copilot backend handling 12k+ concurrent queries at 99.9% uptime. Deep on orchestration (Langflow/Airflow/Kubernetes), reliability evaluation (hallucination detection, p95 latency, token cost), and monitoring (Prometheus/Grafana), with demonstrated stakeholder-facing analytics delivery via Tableau.”

“Entry-level candidate who built NYC Lens, a real-time Gemini-based multi-agent system that processes live camera input, identifies landmarks, and returns structured contextual insights. Despite being a fresher, they show hands-on experience with deployment on Cloud Run, modular orchestration, noisy-data handling, and reliability patterns like retries, fallbacks, and explicit state management.”

Aaron Rodrigues

Screened

Junior Business & Data Analyst specializing in FinTech and banking analytics

Jacksonville, FL5y exp

“Analytics professional with Travelex experience spanning SQL ETL, Python-based machine learning workflows, and Power BI dashboarding in risk, fraud, and AML contexts. Stands out for replacing a $150K+ third-party compliance tool with internal dashboards and for materially improving operational efficiency through alert tuning, cutting alert volume by 50% and false positives by 60%.”

“Full-stack product engineer with hands-on ownership of a B2B e-commerce catalog at Mphasis, spanning React/TypeScript, Java/Spring Boot, and Postgres, with strong evidence of performance tuning and UX improvement. Stands out for tracing production issues across layers, leading an Angular-to-React migration, and pairing product instinct with rapid AI prototyping—placing 2nd in an advanced AI hackathon.”

Anirudh Raj

Screened

Entry-Level Machine Learning & Cloud Engineer specializing in AI data pipelines

Boston, MA

“Early-career cloud/appsec-focused engineer with hands-on experience building secure, observable microservice systems on AWS (IAM least privilege, KMS encryption, Secrets Manager, CloudWatch, ALB) and troubleshooting autoscaling-related 500s down to connection pooling issues. Also deployed heavy ML workloads on Kubernetes by decomposing diffusion/transformer services, using workload identity to eliminate static credentials, and maintaining GitOps-style deployment audit trails.”

“Backend/data engineer with hands-on production experience across FastAPI microservices and AWS (Lambda, ECS, SQS, RDS, S3), plus Glue/Athena analytics pipelines. Demonstrates strong reliability and operations focus (timeouts/retries, centralized errors, CloudWatch monitoring) and measurable SQL optimization impact (25s to under 2s). Seeking fully remote senior developer role at ~$150k base.”

“Backend/data engineer with hands-on AWS data platform work (S3 + Glue + Lambda/Step Functions) and Kubernetes GitOps delivery (Argo CD + GitHub Actions). Has led ingestion and transformation of semi-structured event data, built internal APIs for ETL operations/monitoring, and implemented Kafka-based near-real-time streaming with enrichment and Elasticsearch for search/analytics, plus experience supporting an on-prem ERP migration to AWS.”

“Entrepreneurial product builder who created chaintrigger.com in response to early Web3 demand for real-time on-chain event reactions, offering an alternative to The Graph Protocol and achieving adoption among games and other Web3 projects. Currently developing new tools, dogfooding internally, and building distribution via personal network and a niche Twitter/X following to gather feedback and iterate quickly.”

“Engineering leader for a facial-recognition edge platform who drove a full-stack modernization to scale from ~100 edge devices to thousands of locations. Led a major distributed-systems re-architecture (NATS streaming), database migration (MongoDB to PostgreSQL + TimeScaleDB), and UI/API modernization (React), while scaling the team 5→15 and implementing CI/CD + automated QA to improve release velocity and reliability.”

Saketh Kota

Screened

Mid-level Data Scientist / ML Engineer specializing in Generative AI, RAG, and MLOps

Irving, TX4y exp

“Built and productionized a RAG-based LLM research assistant for biomedical and regulatory document search using Mixtral 7B on SageMaker, LangChain, and Milvus, cutting research time by ~40%. Has hands-on multi-cloud MLOps experience across AWS/Azure/GCP with Kubeflow/Airflow/Composer plus Terraform + ArgoCD, and applies rigorous evaluation/monitoring (latency, accuracy, hallucinations). Also partnered with a non-technical PM to deliver an insurance policy Q&A chatbot that reduced customer response time by 30%+.”