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HomeAt Splunk, that means pairing React product work with Python services, operational data, permissions, evaluation, and release controls. Earlier at Deloitte, I built extraction, storage, API, and visualization systems; two removed more than 36,000 hours of annual manual work and cut investment-processing time by 66%.WritingTechnical writing on software engineering, AI engineering, system design, and the trade-offs behind production systems.ProjectsA growing collection of systems and products I’ve built—from current infrastructure work to earlier projects that shaped how I build today.Abdul AhadI’m an AI full-stack engineer with more than five years of experience building data-intensive enterprise software and production AI systems. At Splunk, I drove AI Service and KPI Discovery from an early prototype through technical design, validation, and production delivery. The capability analyzes operational data and recommends service models and health signals within Splunk IT Service Intelligence.Let’s talk.If you’re hiring, building something interesting, or want to compare notes on a difficult engineering problem, send me a message. A few lines is plenty.ColophonHow this portfolio handles static publishing, search, contact delivery, analytics, and releases.Capacity Planning Before Architecture DiagramsA practical method for turning workload assumptions into request, storage, bandwidth, concurrency, and failure-capacity budgets before choosing an architecture.Design Modules Around Change, Not LayersA practical guide to information hiding, volatile decisions, coupling, cohesion, dependency direction, and avoiding abstractions that preserve the wrong boundaries.From Model Call to Reliable AI WorkflowHow one model request grows into retrieval, tools, deterministic workflows, agents, evaluation, observability, and human escalation.Queues, Backpressure, and Idempotency: Designing for FailureHow bounded queues, admission control, idempotency keys, retry budgets, and dead-letter handling turn asynchronous delivery into a controlled reliability system.Refactoring a Legacy Backend Without a Big-Bang RewriteA staged method for understanding, testing, isolating, replacing, observing, and finally deleting legacy backend behavior without one irreversible cutover.MCP in Production: Trust Boundaries, Permissions, and Tool DesignA production-focused guide to MCP hosts, clients, servers, capability discovery, authorization, consent, token audiences, and safely designed tools.How this portfolio worksA walkthrough of how an edit becomes a published page, what happens after someone presses Send, and how the site avoids losing or saving the same message twice.ThreadsPosts, nested replies, profiles, and communities share the same records. This follows one conversation from creation to deletion.Prompt NexusGoogle sign-in leads to a local user, then one saved prompt powers the feed, profile, search, and edit screens.SeedEditors publish articles in HyGraph, readers receive prepared pages, and new comments remain private until they are approved.CactaOne published video creates a media asset, a post record, and temporary browser state. This follows that upload across the product.System DesignCapacity, queues, failure handling, and distributed-system trade-offs.AI EngineeringLLM workflows, tools, evaluation, permissions, and operations.Software EngineeringModules, testing, refactoring, interfaces, and maintainability.System Design from First PrinciplesCapacity planning, queues, backpressure, retries, and failure handling.Production AI EngineeringModel calls, workflows, tools, evaluation, permissions, and operations.

Software Engineer

Abdul Ahad

I’m an AI full-stack engineer with more than five years of experience building data-intensive enterprise software and production AI systems. At Splunk, I drove AI Service and KPI Discovery from an early prototype through technical design, validation, and production delivery. The capability analyzes operational data and recommends service models and health signals within Splunk IT Service Intelligence.

My career began at Deloitte, where I spent more than three years engineering full-stack data and automation systems across extraction, storage, transformation, APIs, and visualization. I built tools that removed more than 36,000 hours of annual manual work, reduced investment-processing time by 66%, and led small engineering teams from requirements and system design through implementation and release.

At Splunk, I expanded that foundation into enterprise observability and AIOps engineering. I work across React and TypeScript product experiences, Python services, REST APIs, persistent workflow state, operational event and time-series data, role-based access control, telemetry, CI/CD, and automated testing. Beyond AI Service and KPI Discovery, I have delivered capabilities across third-party integrations, incident management, scheduled maintenance, data visualization, governance, performance, and reliability.

My current focus is production AI engineering: LangGraph-based LLM workflows, structured outputs, retrieval-backed context, prompt and schema design, evaluation, observability, guardrails, and resilient failure handling. Outside my primary product work, I designed and built GitSight, an LLM-powered tool for analyzing CI telemetry and recurring test failures; it received first-place recognition in the Developer Productivity category at a Splunk AI Hackathon.

I care about the engineering around the model: clear contracts, correct data, durable state, permissions, failure modes, tests, and operational controls.
36,000+
manual hours removed each year
66%
reduction in investment-processing time
1st
Developer Productivity, Splunk AI Hackathon

Selected experience

From prototypes to production systems

  1. Software Engineer 3

    Splunk

    Nov 2025 — Present

    Own end-to-end engineering for production Generative AI and full-stack capabilities in Splunk IT Service Intelligence (ITSI), spanning React/TypeScript, Python, REST APIs, LangGraph and LLM orchestration, operational data, authorization, evaluation, and observability.

    Originated AI Service and KPI Discovery in ITSI as a hackathon idea, built the initial prototype and demos, and drove its evolution through design, validation, and productionization into a shipped product capability.

  2. Software Engineer 2

    Splunk

    May 2024 — Oct 2025

    Built and shipped full-stack capabilities for Splunk IT Service Intelligence (ITSI), an enterprise observability and AIOps platform, across React and TypeScript applications, Redux/Redux-Saga state architecture, REST APIs, Splunk SPL, data workflows, reliability, and automated testing.

    Built complex product experiences for third-party integrations, incident operations, backup and recovery, scheduled maintenance, and service-health analytics.

  3. Analyst (Software Engineer)

    Deloitte

    Jul 2021 — Apr 2024

    Designed and developed a full stack metrics extraction tool, resulting in a 99% increase in productivity and saving 36,000+ manual hours per year.

    Spearheaded the development of an automated investment tracking application that resulted in a 66% reduction in processing time and saved over 2,000 project hours per year.