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Vetted Communication Professionals
Pre-screened and vetted.
Executive Entrepreneur and Operator specializing in SaaS EdTech and Healthcare Marketing
Senior QA Engineer specializing in automation, API testing, and CI/CD
Senior Sales & Account Management professional specializing in SaaS and hospitality
Senior QA Automation Engineer specializing in web, mobile, and API testing
Mid-level QA Analyst specializing in game performance, optimization, and save systems
Senior QA Lead specializing in mobile and PC game release testing
Lokesh palanivel
Mid-level Customer Service Specialist specializing in technical support and multi-channel service
“Customer-facing application security/support professional who helps teams operationalize SAST/DAST/SCA in CI/CD, reduce false positives, and prioritize remediation by business risk. Has hands-on experience troubleshooting intermittent pipeline failures (rate limiting/timeouts under parallel load) using logs/metrics/traces, and driving durable outcomes via runbooks/KB documentation and phased security rollouts across stakeholders.”
Senior Sales & Marketing Professional specializing in channel marketing and pipeline generation
Senior Graphic Designer specializing in branding, rebranding, and digital marketing assets
Mid-level Industrial Engineer specializing in Lean Six Sigma process optimization
Senior Audio Engineer/Producer specializing in recording, mixing, and live sound
Executive Operations Leader specializing in multi-unit performance and growth
Senior QA Lead specializing in video game testing and post-deployment support
Mid-level Sales Engineer specializing in government bids and CRM optimization
Senior Operations & Sales Leader specializing in digital marketing and IT programs
Mahesh Ponnam
Mid-level Data Scientist specializing in credit risk, fraud detection, and ESG analytics
“AI/LLM practitioner who has deployed production chatbots across e-commerce, HRMS, and real estate, focusing on retrieval-first workflows for factual tasks like product and property search. Optimized intent understanding and significantly improved latency by using lightweight embeddings and tuning the inference pipeline on Groq (Llama 3.3), while applying modular orchestration and measurable production evaluation.”