Beschreibung

I’m a senior cloud and data architect with deep expertise in AWS, distributed systems, and modern data platforms. I help businesses design scalable, high performance architectures, from real time streaming pipelines and data lakes to microservices and AI powered systems.

Recently, I’ve been focused on building production grade GenAI and LLM solutions, including agent based workflows, retrieval augmented generation (RAG), and scalable inference systems.

If you’re looking to turn complex ideas into reliable, cost efficient systems, I bring both hands on engineering depth and architectural vision to get it done right.

Branchenexpertise

Sprachen

Englisch
Muttersprachlich oder zweisprachig

Arbeitsortpräferenzen

Vor Ort möglich

San Francisco (bis zu 50 km), Los Angeles (bis zu 50 km)

FINRA
Principal Architect Data Science
März 2023 - Februar 2025 (1 Jahr und 11 Monate)
Los Angeles, CA, USA
FINRA is the US financial regulatory authority.
• • Architected cloud native data and AI platforms on AWS using warehouse/lakehouse patterns (S3, Glue, Iceberg, Redshift, EMR etc.), enabling analytical, operational, and ML/LLM workloads at scale with enterprise grade security, data governance, and low latency pipeline reliability.
• • Designed and optimized production architectures for LLM/RAG based applications, integrating vector and graph databases with enterprise data platforms, and led collaboration with data science teams to streamline deployment of large language models and agentic workflows.
• • Built microservices and distributed systems using Java, Python, and Spring Boot, containerized with Kubernetes, and exposed through secure REST APIs, API Gateway, and full observability.
• • Architected Kubernetes platforms for stateful, long running workloads and persistent distributed jobs, while establishing architectural standards, enforcing governance through ADRs and design reviews, and managing the engineering delivery roadmap.
• • Spearheaded FINRA wide AI integration standards and data engineering initiatives, defining architectural patterns for compliance, and scalable ML infrastructure across regulatory and analytical domains.
• • Tech: AWS, Microservices, DDD, LLMs/RAG, LangGraph, Hugging Face, Bedrock, MCP, Vector embeddings, and Neo4j; data platforms with Snowflake, Databricks, Iceberg, Glue, EMR, Kafka, and Medallion architectures; Python, Java; cloud native delivery on AWS, Kubernetes, and Step Functions; plus OAuth2, Observability, ADRs, and of course Vibe Coding.
Amazon Web Services Data Lake MCP Kubernetes Apache Kafka
Nike|
Data and modernization Architect
März 2022 - März 2023 (1 Jahr)
Oregon, USA
• • Consolidating enterprise architecture for Nike's internal system for custom clearance.
• • Defined lift and shift strategy for cloud migration to AWS.
• • Re-designed enterprise-wide data flow for high availability and HADR in general.
• • Tech: AWS, microservices architecture, Distributed architecture, Kubernetes, no-SQL, swagger, Kafka, observability, API gateway, API security, Terraform, OAuth2, CI/CD, MongoDB, REST.
Wells Fargo
Architect modernization
März 2020 - März 2022 (2 Jahre)
New Jersey, USA
Led enterprise-wide IT modernization initiative, establishing architectural standards, design patterns, and microservices guidelines for greenfield and legacy system redesigns.
• • Designed monolith decomposition strategy and executed migration of legacy applications to microservices/Modern architecture on AWS cloud platform.
• • Designed data architectures with NoSQL, Aurora, Cassandra, MongoDB; built real time streaming pipelines using Kafka Streams and integrated with Databricks, snowflake for big data solutions.
• • Evaluated legacy systems for cloud readiness, designed serverless architectures using AWS Lambda, and established API security best practices across all development teams.
• • Designed enterprise grade multi region deployment strategies with disaster recovery and high availability, aligned with AWS Well Architected Framework.
• • Tech: AWS, Kubernetes, Docker, Terraform, Istio, Java, Node.js, Spring, Angular, React, Serverless, Event sourcing, CDC, DDD, DynamoDB, Cassandra, MongoDB, AWS Aurora, Parquet, Avro, Databricks, Snowflake, Kafka, REST, GraphQL, OAuth2, API Gateway, Load balancers, API Security, CI/CD, GitHub.