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Tiaa Engineering

To build secure, resilient technology systems enabling lifelong financial security for clients through superior digital experiences and innovative solutions.

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To build secure, resilient technology systems enabling lifelong financial security for clients through superior digital experiences and innovative solutions.

Strengths

  • LEGACY: 100+ years of institutional knowledge and trusted brand
  • PLATFORM: Robust core banking and investment infrastructure
  • TALENT: Strong cybersecurity and compliance engineering teams
  • DATA: Rich historical client financial data spanning decades
  • STABILITY: Financial resources to support long-term tech plans

Weaknesses

  • TECH-DEBT: Aging legacy systems requiring costly maintenance
  • AGILITY: Slow development cycles averaging 12+ weeks per release
  • TALENT: Skills gap in modern cloud and API development expertise
  • INTEGRATION: Siloed systems creating fractured customer journeys
  • ANALYTICS: Limited real-time data processing capabilities

Opportunities

  • DIGITAL: Increasing client demand for 24/7 mobile access (68% growth)
  • API: Open banking standards enabling new partnership models
  • CLOUD: Cost reduction of ~30% through cloud migration initiatives
  • AUTOMATION: Potential 45% reduction in manual operations processes
  • PERSONALIZATION: Data-driven customized financial guidance

Threats

  • FINTECH: Agile competitors with modern tech stacks gaining share
  • SECURITY: Increasingly sophisticated cyber threats targeting finance
  • REGULATION: Growing compliance requirements straining resources
  • TALENT: Industry-wide competition for skilled tech professionals
  • EXPECTATIONS: Rising customer experience standards set by tech firms

Key Priorities

  • MODERNIZE: Accelerate core platform modernization to cloud
  • SECURITY: Strengthen cybersecurity posture against emerging threats
  • TALENT: Close skill gaps in modern engineering practices
  • AUTOMATION: Implement intelligent automation for customer journeys
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To build secure, resilient technology systems enabling lifelong financial security for clients through superior digital experiences and innovative solutions.

CLOUD FIRST

Modernize core platforms for speed, security and scale

  • MIGRATION: Complete phase 1 cloud migration of 40% of legacy systems with zero downtime by Q3 end
  • ARCHITECTURE: Establish microservices framework with 10 core APIs deployed and documented by August 30
  • DEVOPS: Implement CI/CD pipelines reducing deployment time from 5 days to 4 hours across 6 key systems
  • MONITORING: Deploy cloud-native observability platform with 95% service coverage and 99.9% accuracy
SHIELD

Build world-class cybersecurity defense capabilities

  • DETECTION: Implement AI-powered threat detection reducing average breach identification from 72 to 24 hours
  • TESTING: Conduct 12 penetration tests with 95% of critical vulnerabilities remediated within 14 days
  • IDENTITY: Deploy Zero Trust architecture across 80% of internal applications by quarter end
  • COMPLIANCE: Achieve SOC2 Type 2 recertification with zero high-severity findings by September 30
TALENT FORGE

Build engineering excellence through people development

  • SKILLS: Complete cloud certification program with 85% of engineers achieving at least one AWS certification
  • HIRING: Recruit and onboard 12 senior engineers in AI/ML, cloud architecture, and security domains
  • CULTURE: Improve engineering engagement scores from 72% to 85% through technical excellence programs
  • PRODUCTIVITY: Increase sprint velocity by 25% through adoption of shared engineering best practices
SMART OPS

Automate operations for speed, quality and reliability

  • AI-OPS: Deploy predictive maintenance reducing unplanned downtime by 30% across core banking platforms
  • AUTOMATION: Implement robotic process automation for 15 key operational workflows saving 12,000 hours/month
  • ANALYTICS: Launch real-time data analytics platform processing 95% of transactions within 30 seconds
  • EXPERIENCE: Reduce customer service resolution time by 40% through AI-assisted support tools and automation
METRICS
  • DIGITAL ENGAGEMENT: 70% active monthly users on digital platforms (from 62%)
  • RELIABILITY: 99.99% uptime for all critical customer-facing systems
  • VELOCITY: 6-week average release cycle (down from current 10.8 weeks)
VALUES
  • Integrity: We act with honesty and integrity in everything we do
  • Proactive: We anticipate needs and deliver solutions that matter
  • Thoughtful: We consider all angles and impacts before taking action
  • Excellence: We aim for nothing short of excellence in all we deliver
  • Security: We ensure the trust and safety of our customers' data and assets
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Align the learnings

Tiaa Engineering Retrospective

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To build secure, resilient technology systems enabling lifelong financial security for clients through superior digital experiences and innovative solutions.

What Went Well

  • SECURITY: Zero critical breaches despite 22% increase in attack attempts
  • STABILITY: Core systems maintained 99.97% uptime exceeding SLA targets
  • COSTS: IT operational expenses reduced by 7% through initial automation
  • COMPLIANCE: Successfully implemented all regulatory requirements on time
  • TALENT: Reduced engineering turnover from 18% to 14% year-over-year

Not So Well

  • DELIVERY: Product release cycles averaged 10.8 weeks vs 8-week target
  • MODERNIZATION: Cloud migration 3 months behind initial roadmap targets
  • MOBILE: App store ratings remained stagnant at 3.6/5.0 stars (target 4.2)
  • ANALYTICS: Data warehouse migration project 32% over original budget
  • INTEGRATION: API development fell 40% short of planned endpoint targets

Learnings

  • AGILE: Need for improved alignment between business and tech priorities
  • ARCHITECTURE: Monolithic approach creating bottlenecks in deployment
  • SKILLS: Technical debt reduction requires specialized engineering skills
  • TESTING: Automated testing coverage must improve to accelerate releases
  • BUDGETING: More granular estimation needed for modernization projects

Action Items

  • DEVOPS: Implement CI/CD pipeline across all development teams by Q3 2025
  • CLOUD: Accelerate AWS migration with dedicated platform engineering team
  • TRAINING: Launch cloud and microservices architecture training program
  • METRICS: Implement engineering productivity dashboard with DORA metrics
  • AUTOMATION: Increase test automation coverage from current 63% to 85%
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To build secure, resilient technology systems enabling lifelong financial security for clients through superior digital experiences and innovative solutions.

Strengths

  • DATA: Vast proprietary financial data spanning multiple decades
  • COMPLIANCE: Strong governance framework for AI implementation
  • RESEARCH: Established financial modeling expertise applicable to AI
  • TESTING: Robust testing environments for AI model validation
  • PARTNERSHIPS: Strategic relationships with leading AI vendors

Weaknesses

  • INFRASTRUCTURE: Limited AI-ready cloud infrastructure deployed
  • TALENT: Shortage of AI/ML specialized engineers (only 15 of 1200)
  • INTEGRATION: Siloed data limiting AI model training potential
  • ADOPTION: Conservative approach slowing implementation timelines
  • TOOLS: Outdated development tooling hampering AI implementation

Opportunities

  • PERSONALIZATION: AI-powered custom retirement planning solutions
  • EFFICIENCY: 35% potential operational cost reduction via AI
  • RISK: Advanced fraud detection through pattern recognition
  • ENGAGEMENT: Conversational AI increasing digital platform usage
  • INSIGHTS: Predictive analytics improving financial guidance

Threats

  • COMPETITION: Fintech firms deploying AI solutions 3x faster
  • REGULATION: Evolving AI compliance requirements adding complexity
  • BIAS: Risk of embedded bias in financial recommendation systems
  • TRANSPARENCY: Client skepticism toward AI-driven financial advice
  • SECURITY: AI-powered cyber attacks increasing in sophistication

Key Priorities

  • DATA: Unify data architecture to maximize AI model effectiveness
  • TALENT: Accelerate AI engineering hiring and upskilling programs
  • MODELS: Develop retirement-focused AI recommendation systems
  • GOVERNANCE: Establish transparent AI ethics and oversight framework