Dual Career Track Framework
Engineering Track
Technical depth and systems architecture
Engineer I
IC1
Ruby basics
Git workflow
Code review
API testing
Engineer II
IC2
Rails mastery
Python basics
Full-stack JS
API design
Senior Engineer
IC3
System design
AI/LLM integration
CDP architecture
Mentorship
Staff Engineer
IC4
Architecture
Agentic AI
Technical strategy
Cross-org impact
Principal Engineer
IC5
Tech vision
Innovation driver
Industry leader
Strategic influence
Engineering Manager
M1
Team leadership
Hiring
Performance mgmt
Delivery
Director of Engineering
M2
Multi-team lead
Roadmap planning
Budget ownership
Strategy
VP of Engineering
M3
Org leadership
Tech vision
C-suite partner
P&L
🤝 AI Pod Sprint
2-week cycles, joint planning
📋 Code Review Cycles
PM technical context review
🎯 Discovery Workshop
Joint user research, feasibility
🧪 Model Alignment
AI accuracy, bias testing
📊 Data Reviews
CDP integration planning
Product Track
Strategic vision and customer impact
Associate PM
P1
User research
Feature specs
SQL queries
Roadmap support
Technical PM
P2
API design
Tech tradeoffs
Data modeling
Eng collaboration
Senior PM
P3
Product strategy
AI fluency
CDP expertise
Stakeholder mgmt
Group PM
P4
Multi-product
Team leadership
OKR ownership
Platform thinking
Director of Product
P5
Portfolio strategy
Org alignment
Revenue impact
Vision setting
VP of Product
P6
Product vision
Market strategy
Exec leadership
Business outcomes
Core Competency Clusters
AI Fluency
- Awareness: AI basics, use cases
- Application: LLM prompting, integration
- Architecture: Model selection, training
- Innovation: Agentic systems, novel AI
Systems Thinking
- Component: Single feature ownership
- Service: API/microservice design
- Platform: Cross-system architecture
- Ecosystem: Org-wide tech strategy
Stakeholder Communication
- Team: Clear updates, documentation
- Cross-functional: PM/Eng alignment
- Leadership: Executive presentations
- External: Industry thought leadership
Product Empathy
- User awareness: Feature impact
- Customer insight: Pain point analysis
- Market perspective: Competitive positioning
- Strategic vision: Market creation
Reskilling & Upskilling Pathways
Closing the Skills Gap: Legacy to Modern
Structured learning programs addressing critical technology and collaboration deficits
🐍 Python & Modern Backend
- Python fundamentals bootcamp (4 weeks)
- FastAPI & async patterns
- Microservices architecture
- Rails → Python migration strategies
- Data pipeline development
🌐 Full-Stack JavaScript
- Modern JS/TypeScript mastery
- React + state management
- Node.js backend services
- GraphQL API design
- Performance optimization
🤖 AI/LLM Integration
- LLM fundamentals & prompting
- OpenAI, Anthropic API integration
- RAG architecture patterns
- Agentic system design
- AI bias & safety testing
📊 Customer Data Platforms
- CDP architecture fundamentals
- Event streaming (Kafka, Kinesis)
- Data modeling & governance
- Privacy & compliance (GDPR, CCPA)
- Analytics & reporting pipelines
🧪 Testing & Quality Automation
- Test-driven development (TDD)
- CI/CD pipeline optimization
- CodeReview AI integration
- E2E testing frameworks
- Load & performance testing
🤝 Product-Eng Collaboration
- Technical PM fundamentals
- API design for PMs
- Data literacy & SQL
- Agile pod best practices
- Discovery & feasibility workshops
AI Pod Structure: Cross-Functional Project Teams
IFCC Agentic AI Pod
Intelligent Frontline Contact Center
Team Composition
1 Technical PM
2 Senior Engineers
2 Engineers II
1 ML Engineer
1 QA/Test Engineer
Focus Areas
- AI-powered call routing & IVR optimization
- Real-time sentiment analysis integration
- Agent assist copilot features
- Voice biometrics & fraud detection
- Multi-channel conversation orchestration
IFM Analytics & CDP Pod
Intelligent Frontline Marketing
Team Composition
1 Senior PM
2 Full-Stack Engineers
1 Data Engineer
1 Backend Engineer
1 Analytics Engineer
Focus Areas
- Customer data platform architecture
- Real-time attribution modeling with AI
- Conversation analytics dashboards
- Marketing automation integrations
- Predictive lead scoring models
Platform Infrastructure Pod
Shared Services & Developer Experience
Team Composition
1 Staff Engineer
3 Senior Engineers
1 DevOps Engineer
1 Security Engineer
Focus Areas
- Microservices migration framework
- API gateway & authentication layer
- Developer tooling & CI/CD optimization
- Cloud infrastructure (AWS/K8s)
- Observability & monitoring platform
AI Innovation Lab Pod
Emerging Tech & R&D
Team Composition
1 Principal Engineer
2 ML Engineers
1 Applied Scientist
1 Product Strategist
Focus Areas
- Next-gen LLM evaluation & fine-tuning
- Agentic AI system architecture
- Voice AI quality & latency optimization
- Multimodal AI (text + voice + visual)
- AI safety, ethics, bias mitigation
Transformation Impact Metrics
85%
Engineers Reskilled
4
Active AI Pods
60%
Product-Eng Collab Time
92%
Promotion via Skills
-70%
Referral-Only Hires
45%
AI-Enabled Features
6 mos
Avg. Reskill Time
96%
Retention Rate
3x
Deployment Velocity
100%
CDP Migration Progress
