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Vetted AI Engineers in Texas
Pre-screened and vetted in Texas.
Venkat Surimalla
Mid-level Generative AI Engineer specializing in LLM applications and RAG
Mohammed Fariduddin
Mid-level AI Engineer specializing in LLM agents and orchestration
Siyu Xiao
Senior AI Engineer specializing in credit risk modeling and cloud ML platforms
Madhu Koyeti
Mid-level AI Engineer specializing in LLM agents, RAG, and production automation
obulesh policherla
Mid-level AI Engineer specializing in LLM agents, RAG, and MLOps for financial services
Ram Yeturi
Mid-level AI Engineer & Data Scientist specializing in Generative AI, NLP, and Cloud ML
Lekhashree Jeezula
Mid-level Data Analyst and AI Engineer specializing in NLP, RAG, and BI analytics
Punitha Pokala
Junior Generative AI Engineer specializing in LLM agents, RAG, and multimodal AI
Bhuvan Kanigiri
Senior AI/Robotics Engineer specializing in GenAI, LLM serving, and computer vision
Siddartha Sodum
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable inference
Sreeja Akuthota
Mid-level AI Engineer specializing in NLP, MLOps, and predictive analytics
Krishna Teja Kaleri
Mid-level Full-Stack GenAI/ML Engineer specializing in agentic AI and RAG systems
Mahalakshmi Konakanchi
Mid-level AI/ML Engineer specializing in Generative AI and MLOps
“Built and shipped a production RAG assistant using GPT-4, LangChain, and Pinecone/FAISS to search 50K+ institutional documents, with a strong focus on groundedness and hallucination reduction through retrieval optimization and re-ranking. Pairs this with a metrics-driven evaluation/monitoring approach (BLEU/ROUGE, manual sampling, logging) and workflow automation via Airflow, and has experience translating stakeholder needs into iterative AI prototypes.”
Kishor Kashid
Mid-level Full-Stack & Cloud Engineer specializing in AI and AWS
Bhanuja Ainary
Mid-level AI & Machine Learning Engineer specializing in Generative AI, NLP & MLOps
Pranjali Sanjay Shimpi
Mid-level AI Engineer specializing in LLMs, RAG, and production AI microservices
Sneha Ramesh
Mid-level AI/Python Engineer specializing in LLM workflows and RAG
Manoj Kumar Reddy Sodum
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems
Atharva Pandkar
Junior AI/ML Engineer specializing in LLM agents and RAG systems
“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”
Bhanu Kiran
Mid-level Data Scientist & AI Engineer specializing in NLP, LLMs, and predictive analytics
“AI Engineer with production experience building an LLM-powered conversational scheduling assistant (rules-based + OpenAI GPT agents) and improving responsiveness by ~40% through architecture optimization. Strong in orchestration (Airflow), containerized deployments, and data quality (Great Expectations/PySpark), with prior work automating population health reporting pipelines (Azure Data Factory → Snowflake) and delivering insights via Tableau to non-technical stakeholders.”
Varshitha Pendyala
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
“Built a production "Mini RAG Assistant" for internal document Q&A, focusing on grounded answers (anti-hallucination), retrieval quality, and latency/cost optimization. Uses LangChain/LangGraph for orchestration and applies a metrics-driven evaluation loop (including reranking and semantic chunking improvements) while collaborating closely with product stakeholders.”
Atharva Sardar
Junior AI/Software Engineer specializing in LLM agents, RAG, and full-stack ML systems
“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”
Sakshi Jayesh Patel
Mid-level AI/GenAI Engineer specializing in agentic systems and RAG