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Vetted Data Pipelines Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in distributed systems and data platforms
Senior Backend Software Engineer specializing in FinTech and distributed systems
Senior AI/ML Engineer specializing in ML infrastructure and conversational AI
Senior Software Engineer specializing in FinTech compliance systems
Senior UX/Design Research & Innovation Lead specializing in product strategy and venture building
Mid-level Data Engineer specializing in analytics engineering, ML forecasting, and modern data stacks
Mid-level Backend Software Engineer specializing in scalable systems and healthcare workflows
Mid-level Generative AI Engineer specializing in LLMs, NLP, and multimodal systems
Senior Data Engineer specializing in cloud-scale pipelines and legal data utilities
Mid-level Business Analyst specializing in finance, data analytics, and AI infrastructure
Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare IT
Mid-level Software Engineer specializing in financial dashboards and internal tools
Senior Software Engineer specializing in AI-powered backend and data platforms
Senior Software Engineer specializing in full-stack SaaS, AI workflows, and FinTech
Senior Data Engineer specializing in cloud data platforms and big data pipelines
Devisri Veeramachaneni
Senior Software Engineer specializing in cloud backend systems and LLM-powered agents
“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”
Nandini Kosgi
Mid-level AI/ML Engineer specializing in LLMs, RAG, and fraud/risk analytics in Financial Services
“Built and shipped a production-grade GenAI Fraud & Compliance Investigation Copilot for a large US bank, integrating OCR docs, structured data, and prior case history to generate grounded, regulator-friendly summaries and red-flag highlights. Demonstrates strong end-to-end LLM systems engineering (LangGraph/LangChain, hybrid retrieval with FAISS+BM25, guardrails/citations, streaming/latency optimization) plus rigorous evaluation and close partnership with compliance stakeholders.”
Karan Shah
Mid-level Software & Robotics Engineer specializing in autonomous systems and ROS 2
“Robotics software engineer focused on production-grade autonomy in GPS-denied environments, building full navigation stacks (perception, EKF/UKF sensor fusion, planning, control) in ROS2. Integrated YOLOv8/semantic segmentation/RL policies into real-time NAV2 pipelines via a custom perception-aware costmap layer, with emphasis on deterministic control loops, embedded GPU performance, and robust system observability/fault tolerance.”
Mahesh Purushothaman
Senior Director of Software Engineering specializing in cloud-native microservices for streaming platforms
“Engineering leader who drove TiVo IPTV’s client-facing API modernization from a monolith to AWS-based microservices (API Gateway, Lambda, EKS, Kafka, DynamoDB/RDS), including phased/blue-green production routing of millions of calls. Emphasizes org scaling through skill-based hiring, mentorship, and a you-build-you-run ownership culture, while balancing technical leadership with executive stakeholder communication and budgeting.”
Nagatheja Sharaf
Mid-Level Software Engineer specializing in cloud-native systems, automation, and LLM-enabled robotics
“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”