Vetted Problem Solving Professionals

“Organizational effectiveness and L&OD leader with experience managing a global volunteer team and partnering closely with senior leaders to drive enterprise culture change. Demonstrated measurable impact improving employee engagement (+31 points in 6 months) and applying Lean/appreciative discovery to streamline regulatory workflows to meet state-mandated timelines.”

“HR operations and human capital leader with Department of Transportation experience who built an HR policy and training infrastructure from scratch (20 policies in a year), enabling ~25% organizational growth. Known for data-driven process optimization (cut processing time by 20 days and improved request responsiveness by ~20%) and for creating scalable manager enablement tools (HR toolkit/quick-reference guides) while aligning senior leadership and reducing overhead via FTE-to-contractor transitions.”

“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”

“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”

“Talent acquisition leader with experience managing a small recruiting team post-layoffs (1 direct, 3 dotted-line) and staying hands-on in executive search. Led a global expansion to hire 30 roles across the US, UK, and Singapore, and implemented a competency-based, standardized recruiting process for product managers that was validated in real-time and approved by the Chief Product Officer.”

“Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.”

“COO who specializes in professionalizing early-stage/growth operations for sale readiness—at Cooperative Laundry led a major restructuring (40% headcount reduction), redesigned operating hours (24 to 18) to reduce labor cost and improve maintenance uptime, and implemented Lean/Six Sigma systems with KPI-driven operating cadences across multiple sites. Emphasizes cultural transformation ('no surprise' accountability) and mentoring non-ops executives to independently run data-driven operations; cites driving the business to 7x EBITDA and positioning for an acquisition in 2026.”

“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”

“Data-centric operator who supports senior executives by anticipating recurring questions, building lightweight systems (meeting cadence/touchpoints), and driving cross-team clarity through rigorous documentation. Recently managed a staffing plan after significant practice turnover, navigating competing principal expectations and capability gaps while maintaining executive trust and positive feedback through proactive level-setting and discretion with PII/PHI.”

“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”