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Vetted Confluence Professionals
Pre-screened and vetted.
Senior Data Scientist specializing in AI/Deep Learning and applied machine learning
Senior .NET Developer specializing in cloud-native microservices for healthcare and FinTech
Mid-level AI/ML Engineer specializing in GenAI agents and production ML systems
Senior AI/ML Engineer specializing in healthcare LLMs and conversational AI
Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI
Mid-level Machine Learning Engineer specializing in fraud detection and recommendations
Senior Full-Stack Software Engineer specializing in cloud platforms and AI integration
Mid-level AI/ML Engineer specializing in cloud MLOps and GenAI for fraud detection
Senior Game QA Analyst specializing in Unreal Engine testing and release engineering
Karan Mehta
Director-level Business Operations & GTM Strategy leader specializing in analytics and performance
“ZS consultant/product owner who repeatedly turns vague GTM performance goals into decision-centric analytics products and operating rhythms. Has scaled analytics initiatives from pilots into $1M+ platforms with 100+ leader adoption, and tied measurement tools to material business outcomes (e.g., $10M+ incremental revenue impact) through change management and cross-functional alignment.”
Robert Elwell
Executive Engineering Leader specializing in cloud platforms, DevOps, and security
“Senior engineering/CTO-level leader with hands-on delivery of serverless, event-driven cloud governance platforms (deployed across multiple GE business units) and experience building adaptable usage-based billing at UserTesting. Has advised startups (including CaseText during YC) and supported fundraising and acquisition due diligence, including investor materials for a smart cooler custody management system presented to BARDA during Operation Warp Speed.”
Siddhant Sawant
Senior Technical Product Manager specializing in cloud database platforms on Azure
“Has hands-on familiarity with successful F2P mobile fighting games (e.g., Marvel Contest of Champions) and can articulate key retention/monetization systems like streak-based daily logins, gacha rewards, and limited-time events. While not having shipped a game directly, they have shipped web/mobile products integrated into gaming ecosystems and think in terms of live-ops health metrics and A/B testing for IAP offers.”
Poorva Wange
Senior Product Designer specializing in research-driven e-commerce and platform UX
“Product/UX designer with end-to-end ownership of Dell’s “Parts for Your Dell” multi-device shopping experience, using 30+ usability tests and A/B testing to drive a 28% conversion lift and 40% satisfaction increase. Experienced translating complex hardware compatibility logic into guided flows, building cross-viewport design systems, and collaborating closely with engineers on edge cases and component implementation; also prototyped gamified micro-interactions at upGrad and completed a GenZ-focused fintech capstone with PNC.”
Sanskar Gupta
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and cloud microservices
“Backend engineer with hands-on experience building Python/Flask microservices using PostgreSQL/SQLAlchemy, JWT auth, Docker, and GitHub Actions CI/CD. Strong in performance and scalability work—migrated heavy processing to Celery/Redis, tuned queries with EXPLAIN ANALYZE and indexing, and delivered 50%+ API latency reduction. Also integrates AI workflows (OpenAI APIs) with batching/caching/fallbacks and has implemented multi-tenant data isolation patterns.”
Bhagya Sunkara
Mid-level Full-Stack Developer specializing in cloud-native backend services and real-time data platforms
“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”