Vetted Containerization Professionals

“AI/ML engineer (Merkle) with hands-on experience deploying RAG-based LLM applications and real-time recommendation engines into production. Strong in cloud/on-prem architectures, GPU autoscaling, caching, and network optimization—delivered measurable latency reductions (40–70%) and improved retrieval relevance by systematically benchmarking chunking/embedding configurations and validating pipelines via CI/CD.”

“LLM solutions practitioner with SOC/alert-triage experience who takes LLM prototypes to production using RAG (Pinecone), FastAPI services, guardrails, CI/CD, monitoring, and robust fallback logic. Known for rapid real-time debugging of embedding/vector and agent workflow issues, and for driving adoption through code-first workshops and sales-aligned custom demos with measurable improvements (35% faster triage; 40% increase in correct tool usage).”

“Built Hexagon’s production Text-to-CAD Copilot that converts text and rough sketches into editable CAD code, combining GraphRAG (Neo4j/LangChain) with a Gemini-powered vision module and multi-agent geometric validation—cutting manual modeling from a day to ~45 seconds and driving retrieval latency below 50ms. Also has large-scale GCP data/ML orchestration experience (Airflow/Cloud Composer, Dataflow, Pub/Sub, Snowflake) processing 50M+ daily records with drift monitoring and automated reliability controls.”

“Full-stack engineer who built and shipped an AI-powered internal knowledge search system for APL Services, including document ingestion into a vector database, a Python backend, and a React/TypeScript chat-style UI with source citations for trust. Improved production reliability by migrating from Streamlit Cloud to GCP with containerization and scaling controls to eliminate cold-start friction; also co-led a Mensa chapter website redesign as Digital Communications Committee co-chair.”

“Application/security-focused customer-facing implementer who has secured multi-customer data aggregation apps using per-tenant isolation, short-lived/scoped tokens, and vault-based secrets management. Troubleshoots production issues via API gateway logs and performance tuning, and runs repeatable onboarding playbooks with strong customer-specific and cross-project documentation. Emphasizes AWS least-privilege IAM and secure agent deployment patterns, plus container scanning practices that catch vulnerabilities pre-production and build developer trust.”

“Data professional with ~4 years of experience, most recently at AIG (insurance), building ML/NLP systems for fraud detection and policy automation using transformers, CNNs, and clustering/anomaly detection. Also developed a RAG-based knowledge retrieval system, iterating across embedding models and moving to production based on precision and latency SLAs, then containerizing and deploying with SageMaker and CI/CD.”

“Backend engineer with airline operations domain experience who modernized flight-ops systems from batch updates to real-time streaming on AWS (Kafka + Spring Boot microservices), improving latency and stability through metric-driven tuning and idempotency. Also shipped a production LLM decision-support component using RAG over operational logs and internal procedures, with strong guardrails and an evaluation/regression loop to reduce hallucinations and enforce grounding.”

“IBM Power/AIX infrastructure engineer who owned a very large production estate (12 Power9 E980 frames and 400+ AIX 7.2 LPARs) with deep hands-on expertise in VIOS/vHMC, DLPAR, and PowerHA. Demonstrated strong incident response (zero-downtime DLPAR fix; split-brain prevention during storage failure) and modernization skills spanning Jenkins/Ansible CI/CD and Terraform automation for IBM Power Virtual Server/PowerVC.”

Estelle Marcella Bouopda Meba

Screened

Mid-level Full-Stack Developer specializing in React and RESTful APIs

Gatineau, Canada4y exp

“Frontend React/TypeScript engineer who built a text-to-speech feature from scratch end-to-end, including frontend-backend communication and testing. Experienced improving existing React codebases through refactoring into reusable components, custom hooks, and performance optimizations, and collaborates closely with product/design using Figma, design systems, and early previews via staging/Storybook.”

Sabita Kumari

Screened

Senior Full-Stack AI Engineer specializing in LLM/RAG agentic systems

Boston, MA11y exp

“Built and deployed JobMatcher AI, an LLM-driven workflow automation product for job seekers that extracts requirements from job descriptions, matches to user skills, and generates tailored outreach. Demonstrated strong production engineering by cutting per-run cost ~70%, improving reliability with retries/backoff/fallbacks, and reducing hallucinations via schema validation and templating; also orchestrated the system with LangGraph plus Docker Compose across API, vector DB, and workers.”

“Built and shipped an AI-driven interview evaluation pipeline at SeekOut that automated recruiter screening via a multi-stage LLM agent workflow (.NET backend, RabbitMQ orchestration, Python workers). Emphasizes production-grade reliability (idempotency, retries, strict JSON/schema validation), strong observability with OpenTelemetry, and measurable efficiency gains including ~40% reduction in token usage/cost.”

Sai Nikhil Kanchukatla

Screened

Senior Software Engineer specializing in Golang microservices and IAM/SSO

Dallas, TX6y exp

“Backend engineer with experience at DigitalOcean and BNY Mellon, specializing in secure, highly available authentication and API platforms. Built an enterprise SSO system integrating Okta via OIDC with resilience patterns (gRPC contracts, circuit breakers, Kafka) and strong encryption, and led a careful monolith-to-Golang microservices migration using shadow traffic, dual writes, and feature flags to preserve data integrity.”

Rupini Polavarapu

Screened

Senior DevOps Engineer specializing in AWS cloud infrastructure and CI/CD automation

Atlanta, GA10y exp

“AWS platform/infra engineer with hands-on ownership of EKS cluster lifecycle (upgrades, node scaling, networking/ingress, and EBS-backed stateful storage) and reliability validation using Datadog plus CI/CD smoke tests. Also supported on-prem VMware environments and operated a hybrid on-prem-to-AWS setup over site-to-site VPN, including incident response and implementing change-controlled firewall processes and proactive connectivity health checks.”

Emmanuel Bakwowi

Screened

Senior DevSecOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation

New York, NY10y exp

“Cloud/DevOps engineer operating across AWS and Azure, running Kubernetes workloads with secure CI/CD (GitHub Actions/Azure DevOps) and Terraform IaC. Has supported AIX/PowerHA systems in hybrid environments—handling failover testing, incident recovery, and performance troubleshooting (including multipath/storage-path issues)—and has led cutovers by managing dependencies, rollback, and stabilization.”

Kavya Myakala

Screened

Mid-level Frontend Developer specializing in security analytics dashboards

NJ, USA4y exp

“Built and shipped production LLM agents including an end-to-end customer support resolution system (99.9% uptime target) that improved customer satisfaction by ~18% and reduced the need to scale support headcount. Demonstrates strong agent engineering fundamentals—tool-based orchestration, schema-first structured outputs with deterministic validation, and robust eval/monitoring loops—plus experience integrating agents with messy ERP data using canonical normalization and safe fallbacks.”

“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.”

Sai Prathyusha Kanisetti

Screened

Mid-level Software Engineer specializing in distributed systems and healthcare IT

Fairfax, VA3y exp

“Full-stack engineer with experience in both healthcare and transportation, owning products from requirements through production support. Built a secure patient-records pipeline at CORAnet using Spring Boot, AWS S3, Docker, and Terraform, and shipped a real-time operational metrics dashboard at BNSF with Java, React/TypeScript, and Kafka. Stands out for combining backend architecture depth, infrastructure ownership, and pragmatic UI simplification.”

Tyler Brown

Screened

Mid-level Forward-Deployed AI Engineer specializing in LLM automation for financial services

Atlanta, GA5y exp

“Solo builder who created a real-time AI call coaching product for sales reps in just 18 days, spanning 29 stateless edge functions, 157 SQL migrations, and ~72k lines of TypeScript. They combine strong full-stack engineering with sharp product instincts, using direct user feedback and SQL-driven observability to iterate quickly and win early paying customers without marketing.”

“Built an AI-driven trading mentor/analytics system combining a React frontend, Spring Boot backend, and FastAPI ML service for stock risk and indicator analysis. Stands out for a pragmatic approach to AI-assisted development: uses AI for acceleration, but manually reviews code line by line, validates outputs against real market behavior, and adds safeguards for unreliable financial data.”

“Front-end engineer focused on sophisticated enterprise analytics dashboards for business and operations users. They combine strong React/TypeScript architecture with deep browser-performance knowledge and practical UX improvements for demanding expert users, especially in data-heavy applications with large tables, filtering, and role-based workflows.”

“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.”

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%+.”