Role Purpose | Build foundational Python skills and contribute to development tasks under guidance | Independently design and deliver production software and AI solutions | Define AI/ML strategy, architecture, and enterprise standards |
Primary Focus | Learning, execution, reliability | Ownership, quality, delivery | Strategy, scale, influence |
Scope of Work | Individual tasks and features | Features, components, and services | Platforms, products, and org-wide capabilities |
Autonomy | Low Moderate | High | Very High |
Influence | Immediate team | Cross-team | Org-wide, executive |
Coding Expectations (Mandatory) | Writes clean Python code with guidance; debugs basic issues | Independently writes, reviews, and debugs production-grade code | Sets coding standards; reviews critical and high-risk designs |
Machine Learning (Mandatory) | Basic understanding of ML concepts | Designs and implements ML solutions | Defines ML strategy and architecture |
LLMs / Advanced AI (Mandatory) | Awareness only | Production experience desirable but not required | Deep expertise required |
System / Platform Design (Mandatory) | Not expected | Participates in design discussions | Owns and defines architecture |
SDLC & Security (Mandatory) | Follows established standards | Enforces best practices | Defines standards and governance |
Problem Solving | Resolves well-defined problems | Solves complex, ambiguous problems | Anticipates systemic risks and opportunities |
Collaboration | Works with guidance from senior engineers | Collaborates across product, data, and infra | Leads cross-functional and cross-org initiatives |
Mentorship | Receives mentorship | Mentors junior engineers | Develops senior talent and technical leaders |
Executive Interaction | None | Limited / indirect | Trusted advisor to executive leadership |
Decision-Making | Task-level decisions | Technical and design decisions | Strategic, architectural, and investment decisions |
Required Experience | 3-5 yrs experience | ~5+ years or equivalent depth | ~10+ years including leadership |
Nice-to-Have (Examples) | ML coursework, APIs, cloud exposure | LLMs, RAG, vector DBs, financial services | Thought leadership, AI benchmarking, domain mastery |
Not Expected | Architecture ownership, executive communication | Org-wide strategy ownership | Task-level execution |
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