Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am a Senior AI Engineer with 9+ years of experience building predictive, agentic, and generative AI systems that transform large, complex datasets into real-world decision intelligence. I specialize in mining historical operational, regulatory, and audit data to predict risks, recommend preventative actions, and automate compliance workflows. I have led end-to-end AI initiatives, architected expert systems and agentic reasoning engines, and driven scalable cloud deployments across AWS, Azure, and GCP. In my career, I’ve mentored junior engineers, delivered scalable AI solutions that cut manual review time, and built domain-specific NLP and regulatory intelligence pipelines that improve compliance accuracy. I thrive on turning complex business problems into pragmatic, reliable AI-powered workflows that empower teams to act with confidence.…I am a Senior AI Engineer with 9+ years of experience building predictive, agentic, and generative AI systems that transform large, complex datasets into real-world decision intelligence. I specialize in mining historical operational, regulatory, and audit data to predict risks, recommend preventative actions, and automate compliance workflows. I have led end-to-end AI initiatives, architected expert systems and agentic reasoning engines, and driven scalable cloud deployments across AWS, Azure, and GCP. In my career, I’ve mentored junior engineers, delivered scalable AI solutions that cut manual review time, and built domain-specific NLP and regulatory intelligence pipelines that improve compliance accuracy. I thrive on turning complex business problems into pragmatic, reliable AI-powered workflows that empower teams to act with confidence.

Justin Wade Blankenship

AI Engineer, Data Scientist, Developer, +3





I am a Senior AI Engineer with 9+ years of experience building predictive, agentic, and generative AI systems that transform large, complex datasets into real-world decision intelligence. I specialize in mining historical operational, regulatory, and audit data to predict risks, recommend preventative actions, and automate compliance workflows. I have led end-to-end AI initiatives, architected expert systems and agentic reasoning engines, and driven scalable cloud deployments across AWS, Azure, and GCP. In my career, I’ve mentored junior engineers, delivered scalable AI solutions that cut manual review time, and built domain-specific NLP and regulatory intelligence pipelines that improve compliance accuracy. I thrive on turning complex business problems into pragmatic, reliable AI-powered workflows that empower teams to act with confidence.…I am a Senior AI Engineer with 9+ years of experience building predictive, agentic, and generative AI systems that transform large, complex datasets into real-world decision intelligence. I specialize in mining historical operational, regulatory, and audit data to predict risks, recommend preventative actions, and automate compliance workflows. I have led end-to-end AI initiatives, architected expert systems and agentic reasoning engines, and driven scalable cloud deployments across AWS, Azure, and GCP. In my career, I’ve mentored junior engineers, delivered scalable AI solutions that cut manual review time, and built domain-specific NLP and regulatory intelligence pipelines that improve compliance accuracy. I thrive on turning complex business problems into pragmatic, reliable AI-powered workflows that empower teams to act with confidence.

Available to hire

I am a Senior AI Engineer with 9+ years of experience building predictive, agentic, and generative AI systems that transform large, complex datasets into real-world decision intelligence. I specialize in mining historical operational, regulatory, and audit data to predict risks, recommend preventative actions, and automate compliance workflows. I have led end-to-end AI initiatives, architected expert systems and agentic reasoning engines, and driven scalable cloud deployments across AWS, Azure, and GCP.

In my career, I’ve mentored junior engineers, delivered scalable AI solutions that cut manual review time, and built domain-specific NLP and regulatory intelligence pipelines that improve compliance accuracy. I thrive on turning complex business problems into pragmatic, reliable AI-powered workflows that empower teams to act with confidence.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Senior AI Engineer at Noogata

May 1, 2025 - May 1, 2025

Developed and optimized generative deep learning models for image synthesis, text generation, and content creation, ensuring high quality and relevance in real-world applications. Led the integration of generative AI pipelines with cloud infrastructure, enabling seamless deployment and scalability across industries. Collaborated with product managers and engineers to translate business needs into technical specifications, aligning AI solutions with client objectives and improving user engagement. Established a real-time performance monitoring system to track model quality and efficiency, enabling proactive updates. Applied ensemble learning techniques to refine outputs, achieving a 15% improvement in performance. Conducted A/B testing and data-driven experiments to assess impact on user experience and business metrics. Built and maintained a model repository using MLflow and GitHub to support collaboration. Leveraged NLP techniques to enhance text generation and automate content creati

AI Engineer at AutomationEdge Technologies Inc.

May 1, 2022 - May 1, 2022

Developed predictive models for generative applications in IT operations, automating incident response and root cause analysis using AI-driven approaches. Built AI-powered solutions for natural language generation and automated content creation, enhancing customer service operations by reducing response times by 40%. Implemented anomaly detection algorithms for detecting unusual patterns in system outputs, providing real-time alerts to improve operational security. Worked with data engineering teams to develop data pipelines using Apache Spark and Airflow to train generative AI models for text, speech, and image synthesis applications. Designed and deployed generative recommendation systems that personalized system optimizations based on user behavior, improving overall customer experience. Led the integration of machine learning models into existing AI systems for automated workflows, enabling more dynamic and personalized user interactions. Conducted model fine-tuning and feature eng

Machine Learning Engineer at Cognizant

October 1, 2020 - October 1, 2020

Developed and deployed generative models to synthesize content, including text and images, and incorporated these models into core Google services to improve user engagement. Built and optimized deep learning-based recommendation systems for personalized content generation, increasing user interaction by 20%. Designed and refined machine learning models for natural language understanding and content generation, improving Google's ability to handle diverse user queries and generate relevant responses. Created generative image recognition models using CNNs, advancing Google's visual search capabilities and enhancing content creation for users. Worked with Google Cloud teams to integrate generative AI models into cloud platforms, enabling clients to generate content at scale while ensuring system scalability and performance. Streamlined ML workflows, automating the content creation process and reducing model deployment times. Applied time-series analysis to forecast trends in user-generat

Software Engineer at Cognizant

January 1, 2018 - January 1, 2018

Led the development of scalable software applications that integrated generative AI systems, enabling real-time content creation in high-traffic environments. Enhanced Google's cloud infrastructure, designing tools to automate the deployment and scaling of generative AI models using CI/CD pipelines. Developed APIs to enable seamless integration between generative AI systems and existing software applications, ensuring a smooth user experience across products. Optimized performance for generative AI systems, reducing latency and enhancing the speed of content generation, resulting in improved user satisfaction. Collaborated closely with cross-functional teams to align AI-generated content solutions with product goals, focusing on improving user engagement and operational efficiency. Integrated ML algorithms for content generation in real-time applications, optimizing the quality of outputs and increasing user interactions. Implemented monitoring frameworks using Prometheus and Grafana t

AI Research Assistant at Lincoln College

May 1, 2017 - May 1, 2017

Conducted research in generative AI models for pattern recognition and creative content generation, pushing the boundaries of what was achievable with existing machine learning algorithms. Worked with faculty and Ph.D. students to design and implement deep learning models focused on generating meaningful outputs for NLP and computer vision tasks. Developed innovative data preprocessing and feature extraction methods, significantly improving the performance of generative models. Published research on generative machine learning methods, including novel approaches to image classification, object detection, and content synthesis. Created and deployed early-stage generative models using TensorFlow and PyTorch, advancing the application of AI in creative domains. Contributed to building an AI-powered recommendation system that personalized content for users, leading to improved engagement. Presented findings at academic conferences, contributing to the research community's understanding of

Senior AI Engineer at Noogata

June 1, 2022 - May 1, 2025

Led development of Generative AI and Agentic AI applications using LLMs, RAG pipelines, tool-calling, and multi-agent systems to automate complex business workflows. Architected scalable ML pipelines, CI/CD workflows, containerized services (Docker, Kubernetes), and cloud deployments across AWS/GCP to support production-grade AI systems. Built custom HenAI-style reasoning agents, domain-specific NLP models, and regulatory intelligence engines that processed millions of documents with high accuracy. Mentored junior engineers, led code reviews, and guided end-to-end SDLC for enterprise AI feature releases.

AI Engineer at AutomationEdge Technologies Inc.

January 1, 2021 - May 1, 2022

Developed Python automation agents, generative components, and ML-powered decision workflows for enterprise operations and IT audit teams. Implemented agent-based orchestration, anomaly-detection models, and predictive systems that proactively identified operational risks. Integrated AI systems with Docker/Kubernetes clusters, automated CI/CD pipelines, and cloud-native infrastructure for reproducible deployment. Collaborated with cross-functional teams to translate business logic into AI-driven automated workflows and intelligent rule engines.

Machine Learning Engineer at Cognizant

April 1, 2018 - August 1, 2020

Built LLM/NLP pipelines, text-analytics models, and recommendation systems used for policy analysis, operational insights, and compliance automation. Developed distributed AI services using Python, PySpark, microservices, and REST APIs, powering internal audit and risk applications. Implemented automated ML build/deploy systems, model evaluation pipelines, and Kubernetes-based deployment workflows. Designed ML components and React-integrated endpoints enabling AI-powered content summarization and classification.

Software Engineer at Cognizant

August 1, 2017 - January 1, 2018

Developed scalable backend services integrating generative and predictive AI models into production environments. Built APIs enabling automated regulatory content retrieval, audit workflow automation, and compliance-oriented recommendations. Implemented cloud-based CI/CD pipelines to support rapid deployment of AI-driven applications used by enterprise clients. Developed containerized tooling for automated data validation, document processing, and audit risk detection.

AI Research Assistant at Lincoln College

September 1, 2016 - May 1, 2017

Researched and built early expert systems, rule-based agents, and ML prototypes supporting automated decision-making in structured domains. Developed Python pipelines for text classification, clustering, and summarization — foundational work for later GenAI/NLP specialization. Created reproducible research environments using Docker/Kubernetes, enabling efficient experimentation for intelligent agents.