AI experiments are easy.
Production systems are not.
UpskillBay is a cohort-based program for engineers who want to design AI systems that operate reliably in real environments — not just notebooks.
LIMITED TO 15 PARTICIPANTS PER COHORT.
The Transition to Implementation
As artificial intelligence moves from research labs to the enterprise, the focus is shifting from model parameters to system reliability. Success now requires a comprehensive understanding of infrastructure rather than just API consumption.
Most educational tracks focus on the logic of models. UpskillBay focuses on the architecture of implementation — solving for governance, scalability, and return on investment in real-world environments.
Orchestrating multi-agent workflows and retrieval systems.
Managing observability in non-deterministic AI environments.
Aligning technical infrastructure with organizational strategy.
A Three-Layer Approach
The fellowship is structured across three functional areas essential for designing and managing AI systems at scale.
Systems Engineering
- —RAG Architecture
- —Agentic Workflows
- —Chain Orchestration
- —Vector Indexing
- —Prompt Frameworks
Infrastructure
- —LLMOps Pipelines
- —Containerization
- —Production Monitoring
- —Cost Optimization
- —Model Serving
Strategy & Governance
- —Risk Frameworks
- —Data Privacy
- —ROI Modeling
- —Ethical Alignment
- —Adoption Models
Participant Profile
This program is designed for engineers responsible for the technical integrity and scalability of AI systems within their organizations.
Software Architects
Engineers transitioning into high-level AI systems design.
DevOps Professionals
Engineers focused on production deployment and system reliability.
Data Engineers
Professionals responsible for indexing and infrastructure pipelines.
PREREQUISITE: 2+ YEARS OF SYSTEM DESIGN OR PROGRAMMING EXPERIENCE REQUIRED.
Implementation-First Model
The fellowship replaces passive learning with active architecture reviews and production labs.
Weekly live technical architecture sessions
Guided implementation and deployment exercises
Peer-level design and code reviews
Industry-Scale Mentorship
Collaborate with practicing engineers who have managed production-scale AI deployments.
MENTOR PROFILES PUBLISHED ON ACCEPTANCE
Selective Admission Process
Application
Technical background and professional goal review.
Screening
System design competency assessment.
Interview
Direct coordination with program leads.
Decision
Formal cohort placement notification.
COHORT LIMIT: 15 SEATS
Program Tuition
₹75,000
16-week cohort · Limited enrollment.
Tuition includes full access to all technical sessions, architecture labs, implementation materials, and the professional peer network.
Design the Infrastructure of AI.
We are selecting candidates for Cohort 01 based on technical proficiency and implementation focus.