Lead Software Engineer, AI Driven Reliability & Support
at Berkshire Hathaway
Posted 19 hours ago
No clicks
- Compensation
- $114,100 – $193,975 USD
- City
- Chicago
- Country
- United States
Currency: $ (USD)
Lead Software Engineer, AI Driven Reliability & Support at Morningstar combines hardcore production engineering with AI-powered diagnosis to reduce resolution time for advisor issues. You will tackle brownfield legacy systems at scale, build AI tooling to detect, diagnose, and resolve incidents, and shape product strategy around service excellence. This role involves working from the Chicago office Monday-Thursday and collaborating with L1/L2 support, product teams, and other engineers in a shared ownership model. You will design diagnostic flywheels, develop agentic AI workflows, and mentor teammates on AI adoption while maintaining production-grade standards.
The Mission
Financial advisors rely heavily on Morningstar’s Direct Advisory Suite and when software breaks, they need instant resolution. Our Delight team transforms support from cost center into competitive advantage by combining hardcore production engineering with AI-enhanced diagnosis to deliver service excellence competitors can't replicate. You'll work on the hardest engineering problems (brownfield legacy systems at scale) while building AI tools that dramatically accelerate problem solving. You'll shape product strategy, not just fix bugs, proving that service excellence drives revenue and sustainable competitive advantage. This position requires working from the Chicago office Monday through Thursday.
This Role Is Ideal If You:
- Excel during production chaos and love being the "fixer" when systems start to fail
- View AI as a force multiplier for engineering work, not a replacement for deep technical knowledge
- Want your work to directly protect hundreds of millions in revenue
- Are energized by brownfield complexity that greenfield developers avoid
- Understands service excellence can be a durable competitive moat
What You'll Do
40-50%: Production Firefighting & Deep Troubleshooting
- Debug urgent production issues across 20+ years of legacy systems (C#, .NET, Python, SQL) with limited documentation and tightly coupled dependencies.
- Manually reproduce customer issues, isolate root causes, and deploy fixes under time pressure while partnering with L1/L2 support teams to resolve high-priority advisor tickets.
- Maintain uptime for mission-critical financial systems is nonnegotiable, requiring careful fixes that avoid downstream risk.
30-40%: Build the Diagnostic Flywheel
You will design and deploy AI agents that continuously improve detection, diagnosis, and resolution. This includes:
- Agentic and MCP powered tools that mine historical RCA to identify patterns.
- Systems that simulate issues, recommend fixes, automate workflows, and reduce dependency on manual troubleshooting.
- Evolving support from reactive (human driven fixes) to proactive (preventing issues before advisors notice).
- Your work will create compounding efficiency gains as the diagnostic flywheel learns and adapts.
10-20%: Strategic Engineering & Product Influence
You will convert recurring support insights into product intelligence, shaping roadmap priorities based on advisor pain points. You’ll contribute PRs across the codebase, reinforcing a culture of shared ownership. You’ll also mentor teammates on AI adoption while upholding production grade engineering standards.
Required Skills:
Production Engineering (Critical)
- 7+ years debugging enterprise production systems under pressure
- Expert troubleshooting across full stack: backend (C#, .NET Core), databases (SQL/NoSQL), AWS infrastructure
- Strong SQL skills for data investigation and manual fixes
- RESTful APIs, microservices, and distributed systems debugging
AI/Agentic Workflows (Growing Importance)
- Hands-on experience building LLM-powered tools (not copy pasting from ChatGPT)
- Understanding of Context engineering, prompt engineering, and other AI nuances
- Experience with agentic frameworks or MCP servers is a plus
- Python for automation and AI tooling
Cloud & DevOps
- AWS proficiency: ECS, Lambda, RDS, DynamoDB, CloudWatch, S3
- Infrastructure-as-code (Terraform, CloudFormation)
- CI/CD pipelines and modern deployment practices
- APM tools (DataDog, New Relic, etc.)
How the work gets done
- Empathy for advisors and support teams - you're solving real human pain, not abstract engineering problems
- Communication: explain technical issues to non-technical stakeholders
- Collaboration: work with L1/L2 support, product teams, and other engineering teams via shared ownership model
- Bias for action: ship fixes fast, learn fast, iterate
Compensation and Benefits
At Morningstar we believe people are at their best when they are at their healthiest. That’s why we champion your wellness through a wide range of programs that support all stages of your personal and professional life. Here are some examples of the offerings we provide:
Financial Health
100% 401k match up to 6% of salary
Stock Ownership Potential
Company provided life insurance - 1x salary + commission
Physical Health
Comprehensive health benefits (medical/dental/vision) including potential premium discounts and company-provided HSA contributions (up to $500-$2,000 annually) for specific plans and coverages
Additional medical Wellness Incentives - up to $300-$600 annual
Company-provided long- and short-term disability insurance
Emotional Health
Trust-Based Time Off
6-week Paid Sabbatical Program
6-Week Paid Family Caregiving Leave
Competitive 8-24 Week Paid Parental Leave
Adoption Assistance
Leadership Coaching & Formal Mentorship Opportunities
Annual Flex Stipend - $1000 annually to cover personal education & well-being expenses
Tuition Reimbursement
Social Health
Charitable Matching Gifts program
Dollars for Doers volunteer program
Paid volunteering days
15+ Employee Resource & Affinity Groups
Total Cash Compensation Range
$114,100.00 - 193,975.00 USD AnnualInclusive of annual base salary and target incentive
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
001_MstarInc Morningstar Inc. Legal Entity
