
Lilian K
Machine Leaning, AI integrations and Web Dev
Skills

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Portfolio
Work experience
DevOps and Integrations Consultant
DataTech Labs® Data Recovery • Freelance
Nov 2022 - Present • 3 yrs 9 mos
Key Responsibilities Automate CI/CD Pipelines: Design, build, and maintain robust Continuous Integration and Continuous Deployment (CI/CD) pipelines to accelerate software release cycles. Infrastructure as Code (IaC): Provision, manage, and scale cloud infrastructure using IaC frameworks like Terraform, CloudFormation, or Ansible. System & API Integration: Connect disparate enterprise applications, microservices, and databases through secure, scalable integration middleware and APIs. Cloud Migration & Orchestration: Architect and migrate workloads to hybrid/multi-cloud environments using containerization platforms like Docker and Kubernetes. DevSecOps & Compliance: Integrate security scans, automated vulnerability testing, and compliance checks directly into early stages of the deployment pipeline. Continuous Monitoring & Alerting: Configure real-time system monitoring, logging, and automated alerting tools to ensure 99.9%+ platform uptime and high performance. MLOps Support: Collaborate with data engineering teams to operationalize machine learning workflows and streamline model deployment into production environments. Client Advisory & Strategy: Consult client stakeholders on DevOps maturity, cloud optimization, and modernizing legacy IT architectures. Incident Response & Root Cause Analysis: Lead automated failover strategies, troubleshoot operational bottlenecks, and conduct post-mortem analysis for system outages. Environment Management & Quality Assurance: Maintain consistency across development, staging, and production environments through automated configuration management.
ML and AI Integrations
Snowflake • Freelance
Oct 2022 - Present • 3 yrs 10 mos
Key Responsibilities Architect AI/ML Solutions: Design and deploy enterprise-grade machine learning pipelines and generative AI solutions natively on the Snowflake Data Cloud. Drive Product Adoption: Guide enterprise clients in adopting Snowflake's advanced AI toolset, including Snowflake Cortex, Snowpark, and Streamlit. MLOps & Pipeline Engineering: Establish robust MLOps practices within client environments for automated model deployment, tracking, and governance. Data Platform Integration: Optimize end-to-end data processing workflows by connecting modern web applications and cloud data platforms directly with Snowflake compute pools. Technical Client Advisory: Serve as a trusted technical advisor to client engineering teams and C-suite executives on scalable data and AI strategies. Custom LLM & Agentic AI Deployment: Architect and fine-tune large language models (LLMs) and custom AI agents tailored to specific enterprise business cases. Performance & Query Optimization: Tune ML models, data pipelines, and SQL/Python workloads to optimize performance and control compute costs on the platform. Cross-Ecosystem Integration: Build secure data integrations and bridges connecting Snowflake with complementary AI frameworks and third-party cloud ecosystems. Technical Enablement & Training: Conduct hands-on technical workshops, code reviews, and proof-of-concept (POC) builds for client developer teams. Quality & Compliance Oversight: Ensure all deployed AI models, data access controls, and technical deliverables meet strict enterprise security, accuracy, and governance standards.