AI Engineer
About The Position
The AI Accelerator team is central to Morningstar’s Generative AI strategy for the Direct Platform. This team builds and scales core systems like the Morningstar MCP Server, MCP Gateway, and Morningstar Agent. Their responsibilities include delivering GenAI capabilities and addressing production-readiness challenges such as document vectorization, caching strategies, system scalability, security, and reliability. They collaborate with the Morningstar Responsible AI Council to ensure systems meet strict standards for guardrails, PII filtering, moderation, and anonymized evaluation pipelines. The team fosters a strong engineering culture focused on impact, problem-solving, collaboration, shared ownership, and continuous learning. As a Software Engineer on the AI Accelerator team, you will contribute to the design, development, and scaling of core services that power Morningstar Direct's GenAI capabilities. You will be involved in the entire development lifecycle, from ideation and design to implementation, deployment, and iteration. The role involves using modern AI-assisted development tools to enhance delivery while upholding high standards for code quality, testing, and documentation. You will work closely with product managers, designers, and engineers to create technically robust and user-valuable systems. This position is suited for individuals who are curious, enjoy exploring new technologies, and proactively learn beyond immediate job requirements.
Requirements
- Strong collaboration and communication skills; direct, thoughtful, and transparent in discussions
- 3+ years of experience with at least one modern object-oriented programming language
- Solid understanding of computer science fundamentals (data structures, algorithms, design patterns)
- Experience building production grade applications using AI-assisted development tools (e.g., GitHub Copilot, Claude Code)
- Experience building production-grade services using GenAI/agent frameworks (e.g., LangChain, AWS Bedrock, Copilot Studio)
- Experience with containerization and deployment (e.g., Docker)
- Experience building and operating production systems, including debugging and troubleshooting
- Experience with relational databases such as PostgreSQL or MSSQL
- Familiarity with cloud platforms (AWS preferred: EC2, RDS, S3, API Gateway)
- Experience working in Agile environments and using tools like Jira
Nice To Haves
- Experience with Python and the PostgreSQL ecosystem
- Experience with event-driven systems, queues, and ETL pipelines
- Familiarity with vector databases and MCP-based architectures
- Interest in financial markets, investing, or fund research
Responsibilities
- Design, build, and enhance scalable services powering the MCP Server, MCP Gateway, and AI Agent
- Own features end-to-end, from concept through production deployment and monitoring
- Collaborate with product and design partners to deeply understand user needs and deliver meaningful solutions
- Contribute to architectural decisions and continuously improve system design and engineering practices
- Write clean, maintainable, and well-tested code with a focus on performance and scalability
- Use logging, monitoring, and debugging tools to maintain high system reliability
- Evaluate new tools and technologies pragmatically, balancing innovation with real product value
- Create and maintain clear technical documentation and user-facing guides
- Mentor teammates and contribute to a culture of knowledge sharing and continuous improvement
Benefits
- Hybrid work environment
- Opportunity to collaborate in-person
- Tools and resources to engage meaningfully with global colleagues
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
