Lead design, development, and deployment of large language model (LLM) based AI capabilities for Mastercard’s products, ensuring scalability, performance, and cost efficiency.
Responsibilities
Design and own architecture for deploying and operating AI capabilities at scale
Develop high-performance Python backend services for LLM inference orchestration
Establish robust LLMOps and MLOps pipelines on Databricks (AWS) using MLflow
Apply traditional ML and statistical modeling in hybrid architectures alongside LLMs
Translate R&D outcomes into scalable production solutions
Requirements
Master's or Bachelor's degree in Computer Science, AI/ML, or Engineering
A Full Stack Development Senior is responsible for owning end to end delivery of full stack solutions across front end, backend, and Azure cloud platforms.
Responsibilities
Own solution architecture across React front end, .NET APIs, and Azure infrastructure
Provide architectural guidance for scalable, secure, and maintainable systems
Review and approve designs for UI, APIs, cloud infrastructure, and integrations
Define and enforce engineering standards, design patterns, and best practices
Ensure proper use of Azure App Service, Azure Static Web Apps, Azure SQL, Azure AD, Key Vaults, and related cloud services
Build and evolve high-scale, resilient integrations with the broader security ecosystem, pioneer AI-native integration patterns, develop scalable libraries and frameworks, and prototype and deploy AI use cases for autonomous risk management.
Responsibilities
Build and evolve high-scale, resilient integrations (APIs, webhooks, streaming data) with the broader security ecosystem
Pioneer AI-Native integration patterns and innovations
Resolve high frictions cases with customers
Develop scalable libraries and frameworks that allow our platform to speak the language of thousands of enterprise security products
Partner closely with R&D and Product teams to define the future of autonomous risk management
A hands-on engineering role blending deep Azure expertise, strong .NET development skills, and the ability to leverage modern AI-based tools to accelerate velocity and innovation.
Compensation
Base Salary Range: $123,000—$155,000 USD
Responsibilities
Design, develop, and maintain Azure-based applications and services using .NET/C#.
Build and optimize cloud-native components including Azure Functions, Azure Storage (Blob/Table/Queue), Azure Service Bus, Cosmos DB, Azure SQL Database, Data Factory, Logic Apps, and Key Vault.
Implement distributed, event-driven, and serverless architectures focused on scalability, reliability, and performance.
Troubleshoot complex issues across APIs, microservices, data pipelines, and Azure-managed services.
Use AI development tools (e.g., Copilot, Cursor, or AI-enabled IDEs) to accelerate coding, testing, debugging, and refactoring.
Design and implement autonomous agents using LangChain, Crew.ai, SK, Autogen and other relevant frameworks; develop and optimize RAG systems; create evaluation frameworks; implement monitoring and logging; develop documentation and best practices; contribute to agent architecture improvements.
Responsibilities
Design and implement autonomous agents using LangChain / Crew.ai / SK / Autogen and other relevant frameworks
Develop and optimize RAG systems for improved information retrieval and response generation
Create robust evaluation frameworks for testing agent performance and safety
Implement monitoring and logging systems for agent behavior
Develop documentation and best practices for agent development
Lead the technical direction and architecture of production-grade agentic systems for medical claim audits, driving design, evaluation, and reliability of LLM workloads.
Compensation
The salary for this position is based on an array of factors unique to each candidate, such as years and depth of experience, skill set, and certifications. The base salary range for this role is [L6 range: confirm with Comp before posting]. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.
Responsibilities
Own the agent architecture and design decisions
Set evaluation strategy with clinical and coding experts
Engineer context at scale for long, noisy medical records
Lead through ambiguity and technical planning
Run systems in production ensuring reliability and cost control
Requirements
Bachelor's in CS, Math, Engineering or a related quantitative field (Master's or PhD preferred)
Nice to have: long-context citation-grounded systems
Nice to have: caching
Nice to have: observability
Nice to have: cost and latency control on LLM workloads
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