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Sajeer Babu
Software Architect focused on how real systems scale, fail, and evolve, especially at early stages where technical decisions compound quickly.
I think deeply about system design under real constraints and production failures, and the gap between architecture diagrams and reality. I favor clarity over complexity.
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Professional Experience and Portfolio

  1. Professional Experience

    Experience: 9+ years designing, evolving, and operating production systems across commerce, fintech, developer tooling, and enterprise systems.

    Expertise: System design, service-oriented backends, runtime and developer tooling, AI-assisted systems.

    Focus: Reliability, operability, and how small architectural decisions compound over time in real production environments.

  2. Runtime & Platform Engineering Latest

    IBM (2025 - Present)

    Working on runtime systems and developer tooling, examining how systems behave under sustained real-world workloads, and how changes propagate through large, long-lived codebases.

    This work sits close to configuration, language tooling, and production operations, where early design decisions often harden into long-term operational constraints.

  3. Distributed Commerce & RFID Platforms

    retailcloud (2018 – 2025)

    Evolved core commerce and RFID systems from tightly coupled implementations into clearer, service-oriented backends as the product, customer base, and engineering team scaled.

    The work focused on defining service boundaries, clarifying data ownership, identifying where integrations failed under real usage patterns, and keeping the platform operable as business and technical complexity increased.

  4. Regulated Banking & Offline Systems

    M2H Infotech LLP (2016 – 2018)

    Worked on banking automation systems shaped by regulatory constraints, offline operation, and strict failure recovery requirements, where correctness and reliability outweighed feature velocity.

    This period strongly influenced how I think about operational discipline, recovery paths, and the gap between planned system behavior and what production systems actually do under stress.

Notes & Observations

Much of my thinking comes from noticing where early-stage systems tend to drift, how assumptions break under real usage, how responsibilities blur as teams grow, and how small design decisions compound in production.

Some of these observations are written down and shared publicly through short notes on LinkedIn.

Talks

  1. Focuses on architectural decisions that hold up under rapid change — imperfect requirements, small teams, and the realities of scaling before systems are fully understood.
  2. Explores how real-world constraints shape system design, and why many "best practices" need to be re-evaluated once systems face production load and operational pressure.
  3. Looks at where AI genuinely helps developers today, where it creates friction, and how teams adapt when AI becomes part of everyday engineering rather than a novelty.