Senior .NET Developer & Consultant · Dubai, UAE

AI-driven .NET development. Human in the loop.

I’m a Senior .NET Developer and Consultant with over 10 years of experience building enterprise systems. I use AI tools to move faster through analysis, coding, testing, and documentation. Every change still gets an engineer’s review, and nothing ships until it passes the security checks in the pipeline.

Get in touch See how it works
  • 01AI-accelerated analysis, code, tests, and docs done faster
  • 02Human-approved every change reviewed before it merges
  • 03Secure by design automated security checks at each stage
C# ASP.NET Core Angular SQL Server AWS Docker Claude Codex

Profile / 01

I build software that stays in production.

My work covers architecture, hands-on development, integrations, security, and cloud delivery. I use AI where it saves real time, and leave it out where it doesn’t.

I’m Ghaias Ud Din Mehmood, a Senior .NET Developer and Consultant based in Dubai.

For over 10 years I’ve built enterprise applications and secure APIs in .NET, with Angular frontends and SQL Server databases behind them. Along the way I’ve worked on healthcare systems, payment integrations, business process automation, and legacy modernization, and deployed to AWS where projects needed it.

Today Claude and Codex draft much of the first pass, and I decide what survives. Architecture, merge approvals, and release decisions stay with an engineer who is accountable for them. Security checks run automatically in the pipeline, so nobody has to remember them. And I only use AI within approved tools and data boundaries.

  • 10+Years building production software
  • 10+Enterprise production systems I’ve helped build, still in use today
  • 15+Services migrated in a multi-team organizational split, with zero post-migration incidents

Expertise / 02

Enterprise .NET engineering, modernization, and applied AI.

Most of my work falls into three areas: enterprise application development, legacy system modernization, and applied AI. Database design, API integration, cloud and DevOps, and application security run through all three.

01

Build

Enterprise application development

Production .NET and Angular applications built to scale, easy to monitor, and maintainable for years.

  • ASP.NET Core applications and APIs
  • Application database design in SQL Server
  • Authentication, authorization, and least privilege
  • Unit, integration, and end-to-end test automation
  • Cloud and DevOps with Docker, CI/CD, and AWS
  • Business process automation and scheduled jobs
02

Modernize

Legacy system modernization

Working through older systems carefully: adding stable APIs, migrating data with integrity checks, and moving to a cleaner architecture step by step.

  • Legacy .NET modernization
  • API integration with internal and third-party systems
  • Application data migration with integrity checks
  • Performance and application security hardening
03

Accelerate

AI-enabled product engineering

Adding generative AI to products where it saves measurable effort, with limited data access, testing before release, and a person to escalate to.

  • AI features in enterprise applications
  • Conversational chatbots
  • AI-assisted engineering workflows
  • Evaluation, fallback, and escalation design

Architecture depth

Architecture that holds up after launch.

For me, architecture means making trade-offs explicit: how the system will change, how it fails, how its data stays consistent, and how it’s secured and run.

01

Boundaries and evolution

Choosing between modular and distributed designs based on how the domain changes, expected load, team ownership, and deployment needs. API contracts stay versioned.

02

Data and consistency

Planning transactions, idempotency, migrations, and audit requirements up front, so consistency problems don’t show up by accident in production.

03

Resilience and operations

Timeouts, retries, health checks, telemetry, backups, and rollback paths designed as part of the build.

04

Security and delivery

Threat models, least-privilege access, secure configuration, and release gates that block on security findings.

Delivery system / 03

Human-in-the-loop AI delivery

AI takes on the repetitive parts of each stage. Decisions stay with an engineer, and automated security checks run throughout.

  1. 01Discover

    Turn requirements into a clear plan

    AI does
    Drafts requirements, domain models, and threat model
    Human checkpoint
    Scope and acceptance criteria approved
    Security gate
    Threat model and data classification reviewed
  2. 02Build

    Speed up implementation

    AI does
    Generates code and tests from approved specs
    Human checkpoint
    Every pull request reviewed before merge
    Security gate
    Secret scanning, SAST, and dependency checks in CI
  3. 03Verify

    Prove quality before release

    AI does
    Assists with end-to-end and edge-case test generation
    Human checkpoint
    Test evidence and findings reviewed
    Security gate
    DAST, SBOM, and release sign-off
  4. 04Ship / operate

    Release safely and keep improving

    AI does
    Summarizes logs, alerts, and incidents
    Human checkpoint
    Release approval and rollback decisions
    Security gate
    Least-privilege access, IaC checks, and audit trail

Want to see how this would work for your team?

Get in touch

Applied AI / 04

Where AI fits in enterprise systems

The model is only one part. What makes AI reliable in a business system is limited data access, ongoing measurement, and a fallback for when the model gets it wrong.

Conversational systems

AI-powered chatbot for public appointment booking

I worked on an AI-powered messaging chatbot used extensively by a public-sector organization for appointment booking, including during periods of very high demand. My part was the booking flows: building them out and extending them with new options over time.

  • Conversational AI
  • Messaging
  • Appointment booking
  • Patient services
  • Public sector

Engineering

AI-assisted delivery workflows

Claude and Codex for analysis, coding, refactoring, tests, and documentation, working within the repository’s standards, with an engineer approving every merge.

Application security

Secure the system around the model

Securing everything the model can reach: authentication, authorization, secrets, data boundaries, and security scanning across the application around it.

AI safety

Measure AI behavior

Test sets, quality thresholds, cost and latency tracking, and a fallback when results start to drift.

Experience / 05

Selected work and focus areas

Details are kept general to respect confidentiality.

Selected work

Migration lead · Multi-team split

Zero-incident migration of 15+ services, including patient-critical systems

During a multi-team organizational split, I led the migration of the services my team owned. I mapped dependencies and data ownership, planned phased cutovers with rollback paths, validated data integrity at each step, and coordinated with the other teams involved.

OutcomeZero post-migration incidents across all services I was responsible for.

Human-in-the-loop AI delivery

≈70% less elapsed delivery time

On a project estimated at 8 weeks, I used an AI-assisted workflow with human review at every step: AI-aided analysis, reviewed code generation, tests written alongside features, and security scanning in the pipeline.

OutcomeDelivered in about 2.5 weeks instead of 8.

Solution areas

01

Enterprise platforms

Resource and operations management

Full-stack .NET and Angular systems for business workflows, access control, and reporting.

  • ASP.NET Core
  • Angular
  • SQL Server
02

Cloud modernization

Legacy-to-cloud delivery

Containerizing applications, automating deployments, and planning moves to the cloud.

  • AWS
  • Docker
  • CI/CD
03

Connected systems

API and multi-system integration

APIs and middleware connecting internal platforms, external services, payment flows, and legacy data, with authentication and validation at every boundary.

  • Web API
  • Integration
  • Security
04

Process automation

Automated workflows and legacy modernization

Automated recurring business processes such as enterprise staff bonus disbursement, and led the analysis and modernization of undocumented legacy systems.

  • Automation
  • Legacy analysis
  • Modernization

Start / 06

Have a delivery bottleneck or an AI use case?

Tell me what you’re working on, what you want to achieve, and any deadlines or constraints. I’ll reply with a practical way forward.

Best fit: new builds, modernization, integrations, and AI projects that need proper review and auditing.

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