Vetted Requirements Gathering Professionals

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”

“Talent Acquisition/Talent Operations leader who has managed multi-site teams (8–15) and rebuilt high-volume recruiting workflows end-to-end, combining process rigor (structured intake, SLAs, standardized interview kits) with deep ATS analytics. Hands-on with Lever and Workday Recruiting, and led a Workday + GoodTime implementation delivering major efficiency gains (40% scheduling improvement, 50% less manual coordination) alongside measurable hiring outcomes (33% faster time-to-fill, 42% increase in DEI hiring).”

“Worked at easybee ai building a production-grade "voice of the customer" LLM intake agent, hardening a fragile sandbox prototype with JSON-schema constrained outputs, Python/FastAPI validation middleware, and automated retries. Strong in real-time debugging of agentic workflows (snapshot isolation, modular tracing) and in implementing safety/compliance guardrails like a content-moderation middleware to support enterprise adoption.”

“Backend engineer who built a containerized Flask service powering an engineering metrics dashboard by syncing GitHub and Jira data into PostgreSQL, with strong emphasis on schema design, query performance, caching, and background processing. Has hands-on experience with SaaS multi-tenancy (tenant scoping + Postgres RLS) and integrating AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) and external APIs (OpenAI/Hugging Face/PyTorch).”

“Operations-focused leader/consultant who has built corporate teams from scratch and redesigned customer success vs. implementation workflows for scalable new-client onboarding. Uses structured operational audits (tools, contracts, process mapping) to identify redundancies and automation opportunities, then drives adoption through team buy-in. Also mentors cross-functional leaders and has been retained for post-acquisition systems integration.”

“New grad SDE (AI/ML) who built and deployed an LLM-based chatbot framework used across technology, military, and banking contexts, focusing on model selection tradeoffs (latency vs accuracy) through prototyping and benchmarking. Also built a multi-agent "eaterybot" using PyAutoGen/AutoGen with a manager agent orchestrating specialized agents, and emphasizes rigorous testing with adversarial/edge-case datasets and hallucination checks.”

“Healthcare-focused data engineer/ML practitioner with experience at Lightbeam Health Solutions and Humana building production entity-resolution and semantic similarity pipelines across EMR, lab, and claims data. Uses NLP/ML (spaCy, scikit-learn, BioBERT/LightGBM) plus Snowflake/Airflow and vector search (Pinecone) to improve linkage accuracy (reported 90%) and semantic match quality (reported +12–15%), while reducing manual cleanup by 40%+.”

“Software engineer with Citi Bank experience building real-time fraud validation/scoring for loan processing, spanning Spring Boot microservices and a FastAPI Python service secured with OAuth2/JWT. Delivered React/TypeScript operations dashboards and deployed containerized services via Docker/Kubernetes with Jenkins CI/CD, while also tuning databases (Oracle/Postgres) and handling high-volume latency/scaling issues using ELK, caching, and autoscaling on AWS.”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

“Built and deployed a production-style vision-language pipeline that generates structured medical reports from chest X-rays using BioViLT embeddings, an image-text alignment module, and BiGPT fine-tuned with LoRA, delivered via Streamlit and hosted on AWS EC2. Also collaborating experience presenting EDA findings, feature importance, and model performance to Ford managers while working with vehicle parts data at Bimcon.”

“Backend engineer with Citi Bank experience building and operating a Python/Flask Personal Finance Manager platform at 1M+ transactions/month. Strong in secure API design, database performance tuning (PostgreSQL/Azure SQL), and production reliability (92%+ test coverage, load testing, monitoring). Also integrated an NLP expense-tagging microservice with caching, background workers, autoscaling, and multi-tenant isolation via RLS and tenant-aware JWT.”

“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”

“Worked on CI/CD for a project called NXTFolio, including writing acceptance tests in Cucumber. Also collaborated with customers/operators via weekly check-ins to understand needs and align technical work to requirements.”

“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”

“Computer science capstone project: built a UE5 VR campus virtual-tour simulator using Blueprint scripting, including trigger-box interactions that display building/department info. Spent significant time in QA/playtesting to reduce motion sickness and improve UX, and handled a challenging asset pipeline by converting/optimizing high-detail AutoCAD/scan-derived building models via Blender—ultimately creating a custom plugin to help with conversion.”