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Vetted LangChain Professionals
Pre-screened and vetted.
Senior Machine Learning Engineer specializing in NLP and Generative AI
Senior Software Engineer specializing in AI/ML and LLM-powered applications
Senior Software Engineer specializing in enterprise AI/LLM integration and full-stack systems
Senior Full-Stack Engineer specializing in streaming, personalization, and AI/ML platforms
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Director-level Data & AI Engineering Leader specializing in cloud-native analytics and GenAI
Mid-level Data Scientist specializing in Generative AI and LLM applications
Principal Data Scientist specializing in Generative AI and security analytics
Tolulope Akinlabi
Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk
“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”
Staff Software Engineer specializing in SaaS platforms across Healthcare and FinTech
Brian Gomez
Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision
“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”
Deepak Guntreddi
Mid-level Full-Stack Developer specializing in Java/Spring Boot and React
“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”
Principal Software Engineer specializing in distributed systems, security, and low-latency platforms
Senior AI Full-Stack Engineer specializing in GenAI, RAG, and scalable ML systems
Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps