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Vetted Retrieval-Augmented Generation (RAG) Professionals
Pre-screened and vetted.
Mid-level Data Scientist specializing in Generative AI and LLM applications
Principal Data Scientist specializing in Generative AI and security analytics
Senior Full-Stack Engineer specializing in cloud-native AI SaaS platforms
Madhumita Nagle
Software Engineering Manager specializing in Alexa AI and large-scale distributed systems
“Engineering manager/player-coach in the Alexa media ecosystem who led delivery of a Tier-1 gateway service enabling third-party providers (e.g., Spotify/Pandora) to control playback across users’ Echo devices, driving 10–15% lifts in engagement metrics. Deep in API design, AWS infrastructure choices (EC2 vs Fargate), OAuth/LWA auth flows, and production rigor (security reviews, load testing, feature-gated dial-ups), with demonstrated incident ownership and operational automation wins.”
Staff Software Engineer specializing in SaaS platforms across Healthcare and FinTech
Senior Full-Stack AI Engineer specializing in LLM/RAG and production ML platforms
Jayaprakash Majji
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference
“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”
Vishanth Iyer
Senior AI/ML Engineer specializing in LLMs, multimodal AI, and scalable MLOps
“ML/NLP engineer with experience at NVIDIA and Cruise building production-grade AI systems across genomics/biomedical research and autonomous vehicle data. Has delivered multimodal LLM pipelines, large-scale entity resolution, and hybrid semantic search (BERT embeddings + FAISS + Elasticsearch), with measurable impact (≈40% accuracy/retrieval gains; ≈30% data consistency improvement) and strong MLOps practices (Kubernetes, CI/CD, MLflow, Prometheus/Grafana).”
Executive AI/IoT Engineering Leader specializing in full-stack and edge AI systems
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Staff Full-Stack Software Engineer specializing in distributed systems and healthcare platforms
Senior Research Scientist specializing in LLM verification and fraud/risk modeling
Executive Technology Leader specializing in SaaS platforms and Generative AI
Mid-Level Software Engineer specializing in Cloud SRE and LLM-powered automation
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps
Senior Full-Stack Software Engineer specializing in FinTech payments and risk systems
Senior Software Engineer specializing in Python, cloud infrastructure, and AI-powered search