Experience

Hands-on delivery, technology leadership, and accountable solution ownership

My experience spans application development, cloud and production operations, team guidance, architecture decisions, AI-assisted delivery, validation, and operational handover.

Career progression at Medtigo

From full-stack development to board-appointed director

  1. 01
    Stage 1

    Full-Stack Developer

    Built and maintained business applications across frontend, backend, databases, APIs, and deployment environments.

    • Application development
    • API and database work
    • Debugging
    • Deployment support
    • Production issue resolution
  2. 02
    Stage 2

    Cloud and Operational Responsibility

    Expanded into Linux, cloud infrastructure, deployments, system reliability, troubleshooting, and production continuity.

    • Cloud environments
    • Linux administration
    • Deployment workflows
    • Monitoring and reliability
    • Production troubleshooting
  3. 03
    Stage 3

    Technology Function Development

    Helped establish stronger delivery practices, technical ownership, infrastructure discipline, and collaboration between business, product, operations, and engineering.

    • Delivery processes
    • Technical standards
    • Cross-team coordination
    • Requirements translation
    • Operational ownership
  4. 04
    Stage 4

    Director of Technology

    Progressed from direct implementation into guiding technology delivery, reviewing technical direction, removing blockers, supporting engineers, and remaining accountable for whether solutions worked in practice.

    • Team guidance
    • Technical decision review
    • Delivery accountability
    • Architecture direction
    • Stakeholder communication
    • Operational continuity
  5. 05
    Stage 5

    Board-Appointed Director

    Rahul was formally appointed as a board director, reflecting organisational trust and broader responsibility after progressing through hands-on development and technology leadership.

At Medtigo, my role progressed from hands-on full-stack development into broader technology leadership. My responsibilities expanded across application delivery, cloud infrastructure, production operations, technical direction, team guidance, and coordination between business and engineering.

A major part of my work was helping the team solve difficult problems. I translated business concerns into technical direction, helped identify root causes, reviewed implementation choices, removed delivery blockers, and remained accountable for whether the final solution worked in practice.

Cross-functional problem solving

How I solve unfamiliar problems

I work effectively when a problem crosses product, software, cloud, security, data, and operations. My strength is understanding the complete system, identifying the real constraint, guiding the appropriate implementation, and validating the result in the operating environment.

Understand the system

Map the users, business objective, dependencies, data flow, constraints and failure modes before selecting a solution.

Identify the real constraint

Separate symptoms from root causes and determine whether the real issue is architecture, process, data quality, permissions, cost, reliability or unclear ownership.

Guide implementation

Contribute directly where appropriate and work with engineers or specialists where deeper expertise is required, while maintaining the full-system view.

Validate the result

Use tests, raw evidence, operational checks, failure scenarios and user feedback instead of assuming that implementation means readiness.

Breadth with accountable depth

Where I have depth, and where I work with specialists

Core depth

  • Solutions and platform architecture
  • Cloud, operations, reliability and deployment
  • AI-enabled workflow and product delivery
  • Technology leadership and delivery ownership

Working knowledge

  • SIEM and endpoint telemetry
  • Semantic matching and embeddings
  • Recruitment and approval workflows
  • Agentic development systems
  • SaaS applications
  • APIs and integrations
  • Linux, AWS, Azure, databases and infrastructure
Specialist collaboration

Where a problem requires deep specialist expertise, I work with the appropriate engineer or domain expert rather than pretending to hold every answer. My responsibility is to preserve the full-system view, challenge risks, align the implementation with the business requirement, and remain accountable for the complete outcome.

Applied AI operating workflow

My applied AI operating workflow

  1. Problem framing
  2. AI-assisted research
  3. PRD / TRD / roadmap draft
  4. Human review and correction
  5. Controlled task prompts
  6. Implementation review
  7. Testing and evidence
  8. Readiness decision

Frame the problem

Define the business outcome, constraints, users, risks, dependencies, and success criteria.

Challenge AI recommendations

Compare options, inspect assumptions, identify missing context, and reject weak or unsafe recommendations.

Control implementation

Break approved plans into bounded tasks with scope, tests, validation requirements, and hard stops.

Own the outcome

Review the resulting changes, verify evidence, assess failure modes, and remain accountable for deployment and handover.

AI accelerates research and execution. I remain responsible for the direction, review, validation and final readiness decision.
Current direction

I am focused on roles where applied AI, solutions architecture, workflow transformation, cloud operations, and delivery leadership come together — particularly Applied AI Solutions Architect, AI Solutions Engineer, AI Implementation Architect, and AI Delivery roles.

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