Vetted Dashboarding Professionals

“Built a production SQL chatbot for access-log analytics that replaced manual custom report requests with natural-language querying, using LangGraph and a ChromaDB-backed RAG pipeline for grounded, consistent answers. Implemented a privacy-preserving design where the LLM never sees raw customer data (only query metadata) and has experience building multi-agent/tool-calling systems with LangGraph (DeepAgents), including solving sub-agent communication drift via self-reflection.”

“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”

“Backend engineer with Morgan Stanley experience building and owning an end-to-end Python FastAPI microservice for high-volume market data used by trading and risk systems. Strong in performance tuning and reliability (PySpark, Redis caching, async APIs), real-time streaming with Kafka, and production operations (Docker/Kubernetes, GitOps-style CI/CD, monitoring). Has led cloud/on-prem migration work across AWS and Azure, including fixing Azure Synapse performance issues via query and pipeline redesign.”

“US Talent Acquisition/Recruiting Ops leader at Funbox (nearly 5 years) who owns end-to-end recruiting operations and ATS strategy, and who successfully pivoted into HR Ops during a 2022 slowdown (payroll, compliance, policies, reporting). Known for building operational rigor at scale—redesigned req approval/1:1 req-to-hire workflows, led Greenhouse→HiBob hiring module implementation in ~4 months, and executed a major hiring blitz (35→75 reqs; ~90% closed; 100+ referrals) across functions including engineering, product, sales, marketing, and frontline support.”

“ML/AI practitioner with hands-on experience deploying models to production and optimizing for low-latency inference using pruning/quantization, with deployments on AWS SageMaker and Azure ML. Has orchestrated end-to-end ML pipelines with Airflow and Kubeflow (ingestion through evaluation) and emphasizes reproducibility via containerization and version-controlled artifacts, while effectively partnering with non-technical stakeholders using dashboards and business-aligned metrics.”

“Candidate states they are very familiar with the venture capital/studio/accelerator landscape and expresses strong willingness to pursue entrepreneurship "at all costs," but did not provide details on a current startup, business plan, fundraising, or prior accelerator/VC involvement during the interview.”

“Paid media/inbound marketer with experience managing high monthly ad spend in EMEA and Spain, including a regulated online betting environment. Built a content-led acquisition approach (YouTube/blog audience building) paired with remarketing and conversion campaigns, optimizing to CPL and lead quality while collaborating with CRM and external teams.”

“People/HR leader with experience supporting globally distributed teams (US, Canada, UK) and partnering with senior leaders on org design and scalable people processes. Implemented a formal performance review program, including manager training and 1:1 coaching, to improve consistency, transparency, and performance conversations as the company grew.”