Woiny Teka

Machine Learning and AI Engineer with expertise in designing, developing, and deploying enterprise-scale

Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) solutions. Strong experience building production-ready AI applications using Python, FastAPI, Pydantic, Vertex AI, Gemini, LangGraph, LangChain,

CrewAI, and LlamaIndex. Skilled in AI agent orchestration, vector databases, BigQuery, Databricks, enterprise data platforms, and cloud-native architectures on Google Cloud Platform (GCP) and AWS. Experienced in

LLMOps, model evaluation, governance, observability, and production deployment of AI systems. Proven ability to collaborate with business stakeholders and translate AI capabilities into measurable business outcomes through scalable, secure, and intelligent solutions.

Machine Learning Engineer, AI/ML & GenAI at Uber AI Solutions (2025-10 – Present)

• Designed and deployed Agentic AI solutions using LangGraph, LangChain, CrewAI, and LlamaIndex for enterprise automation and intelligent workflow orchestration.
• Built production-grade RAG applications leveraging Vertex AI, Gemini Flash, vector databases, and semantic retrieval pipelines to improve response accuracy and business insights.
• Developed scalable AI microservices using Python, FastAPI, and Pydantic for cloud-native machine learning applications.
• Integrated BigQuery, Databricks, and enterprise data platforms to support large-scale AI workloads and advanced analytics.
• Implemented LLMOps frameworks including model evaluation, governance, observability, monitoring, and production deployment practices.
• Collaborated with business stakeholders to identify use cases, translate business requirements into AI solutions, and deliver measurable operational improvements.
• Containerized AI services using Docker and deployed workloads on Kubernetes and cloud environments across GCP.

Machine Learning Researcher at Google (2025-10 – 2025-12)

• Collaborated with engineering and research teams to enhance Gemini AI platform capabilities, supporting large-scale language model development and enterprise AI initiatives.
• Built and evaluated Generative AI workflows using Vertex AI, Gemini Flash, and advanced prompt engineering techniques for intelligent automation and knowledge retrieval.
• Developed Agentic AI prototypes using LangGraph and LangChain to orchestrate multi-step reasoning, tool calling, and workflow automation.
• Designed Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases, semantic search, and embedding models to improve response accuracy and contextual understanding.
• Contributed to AI model evaluation, benchmarking, governance, and responsible AI practices to ensure production readiness and performance optimization.
• Partnered with cross-functional stakeholders to identify business use cases and translate AI capabilities into scalable solutions that delivered measurable business value.
• Worked with enterprise-scale datasets and cloud infrastructure on Google Cloud Platform (GCP), including BigQuery, Vertex AI, and distributed machine learning environments.
• Supported experimentation, model validation, and deployment workflows following LLMOps best practices for monitoring, observability, and continuous improvement.

Senior AI Software Engineer at HireArt (2024-06 – 2025-10)

• Delivered AI/ML solutions using Python, FastAPI, AWS, and cloud-native microservices.
• Built scalable RESTful APIs and integrated AWS services including Lambda, S3, and API Gateway.
• Developed AI-driven automation systems and optimized ML pipelines for improved operational efficiency.
• Implemented distributed data architectures using MongoDB, Redis, and Elasticsearch.
• Enhanced production deployment reliability using CI/CD pipelines, Git workflows, and automated testing frameworks.

Research Assistant at Maharishi International University (2023-01 – 2023-08)

• Conducted research on machine learning models and AI-driven applications for predictive analytics and intelligent automation.
• Assisted in data preprocessing, statistical analysis, and model experimentation using Python and machine learning frameworks.
• Collaborated with faculty and graduate researchers on software engineering and AI research projects.
• Built data pipelines and automated workflows to improve research efficiency and reproducibility.
• Contributed to documentation, technical reporting, and presentation of AI research findings.

Full Stack Developer at ITEX Iowa USA/ World wide (2019-09 – 2022-08)

• Developed secure software solutions for scalable data-driven applications.
• Built RESTful APIs and dynamic front-end systems improving user experience and engagement.
• Collaborated with cross-functional teams to implement new features and troubleshoot production issues.
• Conducted code reviews, performance optimization, and software maintenance across distributed systems.
• Supported backend development using Java, Spring Boot, JavaScript, and cloud-native technologies.

Master of Science in Data Science & Machine Learning – Harvard University

MBA in Software Applications – Maharishi International University

Bachelor of Science in Computer Engineering – Mekelle University