Vetted Adaptability Professionals

“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.”

Christy Tuescher

Screened ReferencesStrong rec.

Director-level Talent Acquisition leader specializing in global workforce strategy

Cary, NC20y exp

“Recruiter with hands-on full-desk experience leading complex executive and engineering searches, including a VP of AI and Engineering hire. Stands out for using AI sourcing tools, funnel and cycle-time analytics, and market compensation data to unblock searches, influence hiring teams, and close difficult offers.”

“Robotics software engineering intern at Bell Labs who overhauled indoor mobile robot localization in a ROS 2 stack, combining EKF + particle filtering with a neural network to handle BLE multipath disturbances. Delivered a major accuracy gain (~50 cm to sub-20 cm), earned a company Innovation award, published a paper, and saw the approach adopted across the company’s robot fleet.”

George Villacis

Screened ReferencesStrong rec.

Mid-level Business Development Manager specializing in financial data for VC/PE

New York, NY6y exp

“Sales/business professional from PitchBook who managed a high-volume pipeline (50–100 opportunities) and drove hundreds of thousands in new business while simultaneously leading cross-functional initiatives, including a product/data dataset implementation and ERG (La Cultura) campaigns. Strong in executive alignment, operational tooling (Salesforce/Asana/Excel), and handling sensitive information with discretion.”

“ML/AI engineer with experience at Uber and Scale AI, focused on customer service automation across both classical NLP and generative AI systems. Has owned systems from experimentation through production on AWS, including LLM fine-tuning, RAG optimization, safety evaluation, and internal Python platform tooling that improved consistency and engineering velocity.”

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”