• Support the digital transformation of mission-critical federal systems • Develop and deliver secure, scalable solutions built on Microsoft Power Platform, Dynamics 365, and Azure Data Services • Design, integrate, and optimize data architectures that power modern business applications • Build scalable, automated solutions that drive value and impact • Create SAS, SQL, Python, and R programs to prepare raw data for NIOCCS • Generate files, split datasets, create data quality reports, and upload files for coding and review • Develop programs for misspelling correction, identify company names, and improve literal quality • Build .NET tools and create Python programs interacting with the NIO API • Develop machine learning workflows and implement OpenAI-based features • Test, debug, and refine NIO API parameters and monitor their performance • Provide support to external partners and ensure production readiness of APIs • Manage inbox and create accounts for new users • Update service account passwords and configuration files • Review logs, fix system issues, and maintain appropriate access levels • Create performance reports and evaluate metrics • Coordinate technical guidance internally and externally • Explore modernization strategies and prepare documentation

• Lead and analyze experiments, discussing their results with a focus on efficiently deploying tested tools and processes across the company. • Research and develop tools, automations, and processes integrated with AI models for various types of work, such as data analysis, design, and software development. • Collaborate with cross-functional teams throughout the company to define and deliver new features. • Specify and influence technical decisions regarding the use of AI technologies at iFood.

• Design, develop, and maintain backend services and APIs using Python, Java, or Go in a cloud-native environment • Build and deploy agentic systems using Claude tool-use, MCP, LangChain agents, and function-calling patterns • Own the development and maintenance of automation pipelines for the product, ensuring reliability, scalability, and continuous improvement • Architect and implement automation pipelines that reduce manual effort across engineering, QA, and operations workflows • Develop internal developer tools and CLI utilities that improve team velocity and code quality • Integrate agent-powered and automation features into existing products — including intelligent document processing, search, and content analysis • Collaborate with product, QA, and platform teams to identify automation opportunities and ship solutions end-to-end • Write clean, well-tested, production-grade code with proper observability (logging, metrics, alerting) • Participate in code reviews, design discussions, and technical documentation

• Develop and evolve data ingestion applications using AWS tools, both in serverless architectures (Glue, Lambda, SNS, SQS, Kafka, etc.) and in architectures using ECS; • Understand technical requirements by participating in inceptions and refinement sessions; • Implement and structure automated tests to ensure the quality of deliverables; • Perform code reviews and production deployments; • Incident management; • Optimize data jobs and pipelines by working on data partitioning, data skew balancing, and performance tuning; • Design and maintain pipeline orchestrations using AWS Step Functions and AWS EventBridge; • Configure and monitor observability using AWS CloudWatch and, preferably, tools like Datadog; • Work with a FinOps mindset, ensuring efficient cloud resource usage and seeking cost optimization opportunities in data solutions.