Oscar C.

Summary: agentic AI infrastructure for Upwork’s AI Platform

• Developed infrastructure enabling LLM-based agents built with LangGraph and CrewAI to reliably interact with internal enterprise systems and complex data sources

• Integrated agents with the AIP Tools Gateway, a JSON-RPC registry service acting as the tools layer between LLM agents and internal tool servers

• Designed agent workers exposing tool descriptors and health endpoints, allowing automatic validation, registration, and invocation of agents as callable tools

• Developed MCP servers for Jira, Backstage, Bitbucket, and Elasticsearch to expose structured enterprise data through the MCP protocol

• Focused on reliability, schema consistency, tool discoverability, health validation, and safe agent- to-system interaction for production AI workflows

• Supported internal AI platform initiatives related to multi-agent orchestration, tool execution, and enterprise integrations

• Promoting Machine Learning models to Production on GCP

Summary: Led design and delivery of Oxy’s Optimization Pillar MLOps platform in AWS ● Designed and implemented MLOps platform integrating AWS (S3, ECS/Fargate, SageMaker, Lambda) with Oxy’s ODAP Lakehouse ● Packaged and deployed Python optimization models (Gurobi/Pyomo) with CI/CD pipelines in Azure DevOps + MLflow ● Built PySpark ingestion pipelines from Kabal APIs, SQL Server, and PI systems into ODAP, ensuring governance and schema validation ● Collaborated with data scientists and IT to enable predictive maintenance and vessel scheduling optimization use cases ● Mentored engineers and defined role skill matrices across MLOps, DevOps, Backend, and QA

Summary: Backend development in Golang and Python ● Developed new integrations with Notification Platform to send emails to 300k+ users ● Implemented concurrency in email send increasing performance by 98% ● Implemented Spam filters in email send increasing performance further by 46% ● Developed client support for Business Experiences team to tap into Notification Platform, making progress towards goal of deprecating integrations with legacy Mailroom messaging. ● Code reviews and various team activities

• Led data product development on the Databricks Lakehouse platform, ensuring efficient data handling and analysis;

• Migrated data from MySQL and PostgreSQL databases using AWS Database Migration Service (DMS) to streamline data management;

• Developed Data Pipelines using Delta Live Tables (DLT) for real-time and batch processing of data;

• Created a Code Generation tool to automatically generate Scala code for Databricks, enhancing development speed and accuracy;

• Proficient in Databricks, Scala, and Python, with a strong focus on scalable data engineering solutions.

• Developed a Reporting API for analyzing large-scale advertising campaigns (Golang, BigQuery)
• Created an Advanced Query Tool in Golang for complex SQL queries, reducing processing time by 50%
• Implemented Data Modeling for forecasting TV Ads performance to extrapolate impressions, increasing revenue by 20%
• Debugged and improved complex queries in BigQuery, reducing overall query complexity
• Enhanced collaboration with the Data Science team by serving as an interface with the Backend team

• Developed Codegen for ML pipelines (Spark, Scala, Python), accelerating data science processes by 10x
• Invented and patented Codegen technology for processing millions of spreadsheet rows in Spark using Excel formulas
• Launched a startup from idea to market within one year
• Increased market reach by developing plugins for Google Sheets and Microsoft Excel
• Successfully developed the AWS Backend using Sagemaker Autopilot, Lambda, EC2, SNS, and SES

• Tech Lead for Data Science and Engineering team (Spark, Scala, Python)
• Managed a team of five data scientists and data engineers
• Developed a Locations indexer, doubling the speed of finding bank branches in India
• Increased market coverage for the Sendmoney product by supporting FP&A analyses in Spark instead of Excel
• Enhanced the effective reach of push notifications by 20% through segmentation analyses in Spark

• Developed the Mendix Cloud platform using a Mendix code generation tool, streamlining the development process;

• Architected robust security protocols for the Mendix Enterprise Cloud Platform, ensuring data protection and compliance;

• Automated parallel firewall installation and configuration across thousands of cloud nodes, enhancing security and operational efficiency;

• Reverse-engineered Mendix code generation to reproduce applications using the open-source WebDSL language, expanding platform versatility and open-source integration.

• Conducted data mining on a Git repository containing 70 Apache projects, extracting valuable insights for analysis;

• Presented the project findings at ApacheCon US in Atlanta, showcasing expertise and contributing to the open-source community.