.png){kind=logo}
Vetted Amazon Athena Professionals
Pre-screened and vetted.
Entry-level Software Engineer specializing in data platforms and backend systems
Mid-level Data Analyst specializing in financial and healthcare analytics
Mid-level Data Scientist specializing in LLMs and applied machine learning
Mid-level Full-Stack Developer specializing in Java/Spring and modern web apps
Mid-level Machine Learning Engineer specializing in forecasting, NLP, and MLOps
Mid-level Data Scientist specializing in NLP, risk analytics, and MLOps
Mid-level Data Scientist specializing in ML, MLOps, and applied risk modeling
Mid-level Data Scientist specializing in GenAI, NLP, and cloud MLOps
Senior Data Engineer specializing in cloud lakehouse platforms for banking and healthcare
Mid-level Data Engineer specializing in cloud data platforms and BI analytics
Mid-level Data Engineer specializing in cloud ETL, streaming, and ML-ready data pipelines
Mid-level Business Analyst specializing in healthcare analytics and interoperability
Senior Data Scientist specializing in ML engineering and cloud analytics
Likitha Kukunarapu
Mid-level Applied AI Engineer specializing in data engineering and healthcare AI
“Built production LLM agents spanning document Q&A, financial insight generation, and ERP-like operational data workflows, with a strong focus on reliability, grounding, and evaluation. Stands out for translating LLM systems into measurable business outcomes, including 70%–80% support workload reduction and a fallback-rate improvement from 18% to 8% through targeted RAG iteration.”
Sai Manikanta Kasireddy
Mid-level Machine Learning Engineer specializing in cloud-native GenAI and RAG systems
“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”
Mid-level Full-Stack Developer specializing in cloud-native microservices and AI/ML integration
Omkarnath THAKUR
Intern AI/Data Scientist specializing in LLMs, RAG, and MLOps
“Internship project at Builder Market: built an end-to-end production multimodal LLM application that estimates renovation/replacement costs from appliance photos (CLIP embeddings) or text descriptions, combining fine-tuning with agentic RAG. Focused heavily on real-world performance constraints—latency and cost—using parallel agent workflows, model routing to smaller/open-source models, re-ranking, and retrieval chunking, and collaborated closely with CEO/co-founders to deliver the solution.”
Yogita Adari
Mid-level AI Engineer specializing in generative AI, multimodal evaluation, and agentic RAG systems
“Built and productionized an agentic LLM automation system for an insurance client to determine medication eligibility, using prompt-chaining plus a RAG pipeline over policy rules and deploying on AWS (Lambda/Step Functions, Bedrock) with a serverless architecture. Addressed major data/schema mismatch issues via a semantic matching pipeline and validated performance through human agreement scoring, A/B testing, KPI monitoring, and confidence-based human-in-the-loop review.”