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Vetted Generative AI Engineers in the DFW Metroplex
Pre-screened and vetted in the DFW Metroplex.
Rohan Chickalkar
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Harish Gaddam
Mid-level AI/ML Engineer specializing in LLM agents and RAG systems
“LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.”
Sahil Patel
Mid-level Applied AI Engineer specializing in GenAI and financial NLP
Hema Sri Nakirikanti
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and multi-agent systems
Sai Sekhar Dharmireddy
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Siva Manikanta Lakumarapu
Mid-level AI/ML Engineer specializing in Generative AI and NLP
“AI/LLM engineer with production experience building secure, scalable compliance-focused generative AI systems (GPT-3/4, BERT) including RAG over internal regulatory document bases. Has delivered end-to-end pipelines on AWS with PySpark/Airflow/Kubernetes/FastAPI, emphasizing privacy controls, monitoring, and iterative evaluation (A/B testing). Also partnered closely with bank compliance officers using prototypes to refine NLP summarization/classification and reduce document review time.”
Nivith Avula
Senior Generative AI Engineer specializing in LLM applications and cloud-native AI platforms
Venkat Surimalla
Mid-level Generative AI Engineer specializing in LLM applications and RAG
Udayasri V
Mid-level Generative AI Engineer specializing in LLM agents, RAG systems, and workflow automation
Bhavana G
Mid-level GenAI Engineer specializing in AI agents and RAG systems
“Built and deployed a production LLM-based RAG agent platform adopted by multiple business teams (Marketing, GTM, Recruiting, Customer Support) to automate knowledge search, Q&A, and content generation. Emphasizes production-grade reliability (grounding/validation/guardrails), rigorous evaluation/monitoring, and cost-aware scaling via model tiering, prompt/retrieval optimization, and caching using LangChain/LangGraph orchestration.”
Venu Devadi
Senior GenAI Engineer specializing in enterprise LLM systems and RAG platforms
Shaheer Shaik
Mid-level AI/ML Engineer specializing in Generative AI and MLOps
Pranav Marla
Mid-level AI/ML & Full-Stack Engineer specializing in LLM agents and generative AI
“LLM/agent builder who shipped a live consumer AI-agent app (kalpa.chat) that visualizes complex reasoning as interactive graphs and abstracts multi-provider model usage via a unified wallet. Professionally has applied LangChain/LangGraph to IVR parsing and to scaling a football video-generation pipeline at DAZN, including shipping a VAR-specific retrieval/order fix via SQL after iterating with a non-technical PM.”
varunreddy kokkanti
Mid-level Data Scientist specializing in Generative AI and NLP
Ramya Jonnala
Principal/GenAI Engineer specializing in LLMs, RAG, and MLOps
“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”
Keerthana Medarametla
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Radhakrishna Revanth Boddupalli
Mid-level Generative AI Engineer specializing in LLMs, RAG, and prompt engineering
Abhishek Kandi
Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps