Vetted Containerization Professionals

Daniel Berhane Araya

Screened

Senior AI/ML Engineer specializing in production-grade LLM systems for regulated finance

Fairfax, VA9y exp

“AI/LLM engineer with published work who built FinVet, a production financial misinformation detection system using multi-pipeline RAG, confidence-based voting, and evidence-backed outputs (F1 0.85, +37% vs baseline). Also built NexusForest-MCP, a Dockerized Model Context Protocol server exposing structured global deforestation/carbon data via SQL tools for reliable LLM tool use. Previously delivered borrower risk-rating (PD) models at BMO Financial Group that were validated and integrated into an enterprise credit system through close collaboration with credit officers and portfolio managers.”

Harshitha K

Screened

Mid-level Full-Stack .NET Developer specializing in cloud-native microservices

Greensboro, NC5y exp

“Full-stack .NET engineer with cloud and applied GenAI experience who shipped a real-time policy status tracking module at Lincoln Financial using ASP.NET Core/.NET 8, Kafka, Angular, SQL Server, Redis, and AKS autoscaling. Also delivered a production internal LLM+RAG support assistant at Honeywell with strong security/guardrails (PII masking, RBAC) and a rigorous eval/regression loop built on a 200-question gold set.”

Swetha Sai

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and analytics platforms

Remote, USA4y exp

“JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.”

Mohithkumar Bolisetti

Screened

Mid-level Java Full-Stack Developer specializing in microservices and cloud platforms

Strongsville, Ohio5y exp

“Full-stack engineer focused on modernizing legacy financial/compliance platforms into cloud-native, domain-driven microservices. Deep hands-on experience across Spring Boot/Kafka/Redis/Postgres-Mongo backends and React/Angular frontends, with strong CI/CD and Kubernetes/OpenShift deployment practices for real-time, high-volume workloads.”

John Chance

Screened

Senior Machine Learning Engineer specializing in conversational AI and healthcare ML

Greenwood, LA9y exp

“ML/AI engineer with hands-on ownership of both classical recommender systems and safety-sensitive LLM agent platforms. They combine production MLOps depth with behavioral health domain experience, including clinical safety validation, explainability, and multi-agent orchestration, and cite measurable impact in both business metrics and latency reduction.”

“Backend-focused engineer with experience at Charles Schwab owning financial workflow deployments end-to-end, including API/database design, SQL optimization, Python automation, and AWS-based production stabilization. Also brings applied AI quality experience through building LLM/agent validation pipelines focused on scenario testing, edge-case detection, and reducing production risk.”

“Junior developer with over a year of experience who is already applying AI-assisted engineering practices in production, including GitHub Copilot, ChatGPT, SonarQube, and OpenAI-based workflows. On a Citibank public portal built with .NET 8 and Angular, they used AI tooling plus CI/CD quality gates to speed delivery and reportedly reduce post-deployment bugs by 30-40% while maintaining strict security and compliance standards.”

Jeffrey Ren

Screened

Mid-level Full-Stack Software Engineer specializing in SaaS and AI-enabled web applications

Henderson, NV5y exp

“Full-stack engineer who led an end-to-end rebuild of a service-agent case management app (React SPA + backend/DB updates) and added Datadog monitoring, improving agent throughput by ~1 case/hour and saving roughly $15K/month. Experienced in incremental legacy modernization (including moving a legacy React frontend toward a Rails-based approach) with heavy unit/E2E testing and strong cross-team stakeholder communication.”

Koushik Ravikumar

Screened

Mid-level Full-Stack Engineer specializing in cloud-native Java and AI platforms

Kyle, TX4y exp

“Full-stack engineer with strong cloud and platform experience spanning React, Go, AWS, Kafka, and Terraform. Has led complex migrations from monolithic/containerized systems to microservices and cloud deployments, built compliance-oriented logging infrastructure, and improved a broken frontend codebase to achieve a 3x performance gain while making it easier for other developers to extend.”

“Backend engineer with experience at KPMG evolving an audit/reporting platform from monolithic components to microservices (Spring Boot/Node.js), improving API performance and enabling independent deployments. Demonstrates strong production focus across secure API design (FastAPI, JWT/OAuth2, RBAC/RLS), incremental migrations with feature flags, and robustness improvements like optimistic locking to prevent race conditions.”

“Backend engineer who built the core backend for Air Kitchens’ discovery/booking platform on AWS (Node + Python, DynamoDB, SQS/Lambda), optimizing for fast user-facing APIs and scalable async workflows. Introduced an AI matching service with a deterministic pre-filter + LLM ranking approach to balance latency vs quality, and has hands-on experience with production security (JWT/RBAC/RLS), CI/CD, and blue-green, staged migrations from Django to modular services.”

“Robotics software engineer focused on system-level C++/Linux stacks for multi-robot platforms, owning the communication layer and validation/testing infrastructure. Built Python simulation/replay and fault-injection tooling integrated with Docker + GitLab CI/CD, and debugged real-time localization issues by instrumenting IPC timing and refactoring multi-threaded pipelines for deterministic performance.”

“LLM/agentic systems practitioner who repeatedly takes customer-facing LLM prototypes into production by operationalizing prompts, hardening RAG pipelines, and adding monitoring/guardrails. Has hands-on experience debugging intermittent production failures under high traffic (vector store timeouts/empty retrieval) and implementing fail-safe behavior plus alerting. Also partners closely with sales in pilots/POCs, customizing demos with customer data and running side-by-side comparisons to drive adoption.”

“Built a production multi-agent orchestration platform to automate healthcare claims and HR workflows, combining LangChain/CrewAI/AutoGPT with RAG (FAISS/Pinecone) and fine-tuned open-source LLMs (LLaMA/Mistral/Falcon) in private Azure ML environments to meet HIPAA requirements. Emphasizes rigorous agent evaluation/observability (trajectory eval, adversarial testing, LLM-as-judge, drift monitoring) and reports measurable outcomes including 35% faster claims processing and 40% fewer chatbot errors.”

“Telecom (Verizon) AI/ML practitioner who built a production multimodal system that ingests messy customer issue reports (calls, chats, emails, screenshots, videos) and turns them into confidence-scored incident summaries with reproducible steps and evidence links. Also built KPI/alarm-to-ticket correlation to rank likely root-cause domains (RAN/Core/Transport), cutting triage from hours to minutes and improving MTTR.”

“Software engineer/product-focused builder who delivered real-time supply chain inventory dashboards to replace a legacy system, integrating directly with ERP/WMS/TMS to eliminate manual reporting. Uses TypeScript/React with Redux Toolkit on the frontend and microservices + REST APIs on the backend, with performance improvements via Redis caching and a strong focus on user-feedback-driven prioritization and observability in distributed systems.”

“Full Stack Developer (recently at Cisco Systems) building end-to-end web applications with Angular frontends and Spring Boot microservices backed by MySQL/JPA, including JWT + role-based access. Has hands-on experience with high-volume, real-time data processing/visualization and has solved complex UI state consistency issues using RxJS BehaviorSubjects; also applies layered state patterns in React with Redux Toolkit and uses AI dev tools (Cursor/Claude) strategically.”

“Graduate student researcher on the EARTH project (college collaboration with Moog) working on robotics for an arm/bucket system. Implemented waypoint-based path planning, built an Apriltag data pipeline, and developed ROS 2 tooling including a joystick-to-DeltaCAN teleop node; exploring reinforcement learning policies trained from Tera simulator + ROS 2 bag data to optimize trajectory planning under varying pressure/load conditions.”

“Full-stack engineer with enterprise experience at Metasystems Inc. (and Qualcomm) building high-traffic, security-sensitive systems—owned a secure transaction processing module end-to-end using Java/Spring Boot, Python/Django, and React. Strong AWS production operations (EKS/ECS/Lambda/RDS/DynamoDB) with IaC (Terraform/CloudFormation), observability, and reliability patterns; also delivered resilient ETL/integration pipelines with idempotency/retries/backfills and achieved a 50% deployment-time reduction through CI/CD and modular refactoring.”

“IBM engineer who built and deployed a production RAG-based LLM assistant using LangChain/FAISS with a fine-tuned LLaMA model, served via FastAPI microservices on Kubernetes, achieving 99%+ uptime. Demonstrates strong practical expertise in reducing hallucinations (semantic chunking + metadata-driven retrieval) and managing latency, plus mature MLOps practices (Airflow/dbt pipelines, MLflow tracking, monitoring, A/B and shadow deployments) and effective collaboration with non-technical stakeholders.”

“Cloud/Kubernetes-focused engineer with production ownership in multi-account AWS environments (GE) and EKS-based platforms (Lumeus.ai). Strong in incident response and reliability—diagnosed IAM-driven serverless failures (SQS/Lambda) and Kubernetes deployment issues (CrashLoopBackOff, memory pressure) with rollbacks, policy fixes, and improved monitoring. Built secure Jenkins CI/CD and delivered infrastructure via CloudFormation and Terraform for serverless and EKS stacks.”

“Infrastructure engineer with hands-on ownership of a scaled IBM Power/AIX estate (AIX 7.x, VIOS, HMC; 2 frames/20+ LPARs) supporting critical middleware and database workloads, including live DLPAR changes and VIOS/SAN outage recovery. Also brings modern DevOps/IaC experience building GitHub Actions pipelines for Docker/Kubernetes deployments and provisioning AWS environments with Terraform (EKS/RDS/VPC/IAM) using modular, review-driven workflows.”