Available for Consulting · Q3 2026

I Build the Infrastructure That Powers AI.

Sachin Diwakar — Software Engineer @ Microsoft. I design and operate the distributed messaging, cloud and AI infrastructure that quietly moves billions of events behind the products people use every day.

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0 Years Engineering
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0 Microservices Shipped
0 Cloud Scale Projects
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About · Why Me

I help teams move from "it works" to "it scales".

For half a decade I've lived inside the hardest parts of distributed systems — message brokers under brutal load, cloud platforms with zero tolerance for downtime, and the AI infrastructure quietly powering the next wave of products.

The story

I started where every great engineer starts — obsessed with fundamentals. Operating systems, networks, data structures. Solved over 1,000 algorithm problems before I ever shipped a feature.

At IBM India Software Labs I spent years on security and mobility platforms — designing message-driven microservice fabrics, identity integrations and secure tunnels for some of the world's largest enterprises.

Today, at Microsoft, I work on the cloud and AI infrastructure that frontier workloads depend on. Same instinct, bigger blast radius.

  1. Microsoft · Software Engineer II

    Building cloud and AI infrastructure that runs at planet scale. The substrate beneath modern AI workloads.

    • AI Infra
    • Distributed Systems
    • Cloud Native
    • Kubernetes
    • Azure

  2. IBM India Software Labs · Software Engineer

    Security & Mobility platforms. Distributed messaging, identity, microservice architecture and platform engineering across products serving Fortune-500 customers.

    • Java
    • Spring Boot
    • Kafka
    • RabbitMQ
    • IBM MQ
    • OpenShift
    • Go

  3. IIIT Jabalpur

    Bachelor of Technology, CSE. 1,000+ algorithm problems. Deep work on operating systems, networking, databases and machine learning.

    • DSA
    • OS
    • Networks
    • AI/ML
    • Databases
Core Expertise

Where I'm dangerously good.

Deep, hard-won expertise in the systems modern AI products quietly depend on — message buses, distributed platforms and the cloud-native plumbing that keeps everything moving.

AI Infrastructure

Frontier

Inference fleets, model serving, vector stores and the event pipelines that feed them. Building the substrate behind production-grade AI.

Distributed Messaging

Specialty

Kafka, RabbitMQ, IBM MQ, Event Streams, NATS. Designing reliable, ordered, exactly-once pipelines that survive partitions, replays and very bad days.

Distributed Systems

Core

Consensus, replication, partitioning, backpressure — the physics of building correct systems on unreliable networks.

Cloud Platforms

Hyperscale

Azure, AWS, GCP. Cloud-native primitives, hybrid topologies and platforms that hum quietly while serving millions.

Kubernetes & OpenShift

Production

Operators (Go SDK), Helm, multi-tenant clusters, GitOps — shipped and operated for years, not weeks.

Microservice Architecture

300+ services

Java / Spring Boot, Node.js, Go. Event-driven boundaries, clean contracts, REST + gRPC, identity-aware routing.

AI Engineering

Applied

RAG pipelines, embeddings, evaluation harnesses, agent orchestration. Practical AI shipped to real users — not just demos.

Observability

Signal

Prometheus, Grafana, ELK, distributed tracing — the difference between "it works" and "we know exactly why."

Reliability Engineering

SRE
99.99%

Error budgets, SLOs, fault injection and incident response that keeps mission-critical platforms standing.

Selected Work

Systems built to scale, survive and stay quiet.

A snapshot of the kind of problems I love — distributed messaging at hyperscale, AI-native platforms, and the cloud-native plumbing in between.

Distributed Messaging

Event Backbone for Enterprise Platforms

Problem

Mission-critical workflows were tightly coupled, hard to evolve and impossible to scale independently.

Architecture

Designed an event-driven backbone on Kafka, RabbitMQ and IBM MQ with idempotent consumers, dead-letter queues, schema contracts and exactly-once semantics.

Impact

Decoupled 100+ services, unlocked horizontal scale, and turned a brittle integration layer into a calm, replay-safe nervous system.

  • Kafka
  • RabbitMQ
  • IBM MQ
  • Spring Boot
  • Avro
AI Infrastructure

AI Inference & Serving Platform

Problem

Teams shipping AI features needed low-latency, multi-tenant inference with predictable cost.

Architecture

Autoscaling inference fleet on Kubernetes, gRPC + streaming APIs, model versioning, batching and observability baked into every hop.

Impact

p99 latency cut significantly while doubling throughput per GPU — and engineers stopped paging at 3 AM.

  • Kubernetes
  • gRPC
  • Python
  • Go
  • Prometheus
Cloud Native

Hybrid Cloud Connectivity Platform

Problem

Large enterprises needed to bridge sensitive on-prem assets (AD, LDAP, PKI) to a multi-tenant cloud — without compromising security.

Architecture

Modular microservice fabric — 300+ services on a hybrid topology with encrypted tunnels, identity-aware routing (SAML, OAuth2, Kerberos) and zero-trust controls.

Impact

Secure, audited connectivity for thousands of enterprise customers under FedRAMP, SOC2 and GDPR.

  • Java
  • Spring Boot
  • SAML
  • OAuth2
  • LDAP
Platform Engineering

Kubernetes Operators & Self-Healing Platform

Problem

Manual lifecycle for critical services meant slow rollouts, drift and weekend incidents.

Architecture

Custom Operators using the Go Operator SDK, declarative Helm charts, GitOps pipelines (Jenkins + GitHub Actions) and policy-driven rollbacks.

Impact

Hands-off lifecycle and self-healing for the most critical services — fewer pages, safer releases.

  • Go
  • Kubernetes
  • OpenShift
  • Operator SDK
  • Helm
Messaging · K8s

Highly-Available Messaging on Kubernetes

Problem

Enterprise messaging needed cloud-native HA, external reachability and strict transport security.

Architecture

Multi-instance queue managers with persistent storage on OpenShift, external routes, mutual TLS and proactive diagnostics.

Impact

Resilient messaging fabric that survives node loss, AZ failures and noisy neighbours — without operator panic.

  • IBM MQ
  • Kafka
  • OpenShift
  • mTLS
  • Event Streams
AI · RAG

RAG & Agentic AI Pipelines

Problem

Turning raw enterprise data into trustworthy AI answers — with evaluation, not vibes.

Architecture

Event-driven ingestion, embeddings, vector store, retrieval + re-ranking and agent orchestration — every hop instrumented and evaluated.

Impact

Production-ready AI workflows with measurable answer quality, cost controls and full traceability.

  • Python
  • LLMs
  • Vector DB
  • Kafka
  • Eval Harnesses
~/sachin/event-platform — zsh 

        

      


      
      

        

           Work With Me
          

            Let’s build something that scales.
          

          

            Whether you’re shipping your first event‑driven platform or scaling AI
            inference to millions of users — here’s how I can help. Reach out and
            I’ll get back within 24 hours.
          

        


        

          

            01
            
Architecture & System Design

            
For teams designing the next big thing.

            
    
              
  • Event‑driven & messaging architectures
    • 
              
  • Microservice decomposition & API design
    • 
              
  • Scalability, HA & resiliency reviews
    • 
              
  • Cloud & Kubernetes strategy
    • 
            

            Start a Conversation
          


          

            02
            Most Requested
            
AI Infrastructure & Inference

            
From prototype to production‑grade AI.

            
    
              
  • LLM serving, autoscaling & cost optimization
    • 
              
  • RAG, embeddings & vector store design
    • 
              
  • Agentic AI pipelines & evaluation harnesses
    • 
              
  • GPU infra, observability & SLOs
    • 
            

            Book a Discovery Call
          


          

            03
            
Distributed Messaging Deep Dive

            
When your event backbone needs to survive very bad days.

            
    
              
  • Kafka / RabbitMQ / IBM MQ / NATS reviews
    • 
              
  • Exactly‑once, ordering & replay strategies
    • 
              
  • DLQs, back‑pressure & consumer health
    • 
              
  • Migration & modernization paths
    • 
            

            Request a Review
          


          

            04
            
Production Debugging & SOS

            
Pager screaming? Latency spiking? Let’s fix it.

            
    
              
  • Distributed systems root‑cause analysis
    • 
              
  • Kubernetes & cloud incident triage
    • 
              
  • Performance & latency investigations
    • 
              
  • Post‑incident hardening
    • 
            

            Get Urgent Help
          


          

            05
            
Mentorship & Interview Prep

            
For engineers aiming for top product companies.

            
    
              
  • Microsoft / FAANG interview coaching
    • 
              
  • System design & LLD walkthroughs
    • 
              
  • Career roadmap & resume reviews
    • 
              
  • 1:1 long‑term mentorship
    • 
            

            Reach Out
          


          

            06
            
Fractional / Advisory Engagements

            
For founders & CTOs building serious infrastructure.

            
    
              
  • Technical strategy & architecture leadership
    • 
              
  • Team mentoring & engineering processes
    • 
              
  • Due diligence & tech audits
    • 
              
  • Hands‑on guidance through critical milestones
    • 
            

            Let’s Talk
          

        


        

          

            
Not sure where to start?

            
Send a short note about your problem — I’ll reply within 24 hours with how I can help (or who else can).

          

          

            Email Me Directly
            Connect on LinkedIn
          

        

      


      
      

        

           Achievements
          

            Numbers that tell a story.
          

        

        

          

            0
            Messages Routed Daily
          

          

            0
            Microservices Architected
          

          

            0
            Algorithm Problems Solved
          

          

            0
            Production Availability
          

          

            Microsoft
            Software Engineer · AI & Cloud Infrastructure
          

          

            Ex IBM
            Security & Mobility · Distributed Platforms
          

          

            Distributed Messaging
            Specialist · Kafka · RabbitMQ · MQ
          

          

            AI Infrastructure
            Inference · RAG · Agentic Systems
          

        

      


      
      

        

           Thought Leadership
          

            Writing on infra, AI and scale.
          

        

        

          All
          AI Infrastructure
          Distributed Messaging
          Distributed Systems
          Cloud Engineering
          Microservices
          System Design
          Career
        

        

          
            AI Infrastructure
            
What "Production AI" Actually Means

            
Inference, evaluation, cost — the things demos never show.

            10 min read
          
          
            Distributed Messaging
            
Kafka vs RabbitMQ vs MQ — A Practitioner's Map

            
Pick the right broker for the right shape of problem.

            9 min read
          
          
            Distributed Systems
            
Backpressure Is a Product Decision

            
Treat queues like contracts, not buffers.

            7 min read
          
          
            Microservices
            
300 Microservices Later — What I'd Do Differently

            
Hard-won lessons from a real enterprise fabric.

            8 min read
          
          
            Cloud Engineering
            
The Three Latencies You Must Measure

            
And the one that quietly destroys cloud bills.

            6 min read
          
          
            System Design
            
Designing for the 99.99th Percentile

            
Tail latency is the customer experience.

            11 min read
          
        

      


      
      

        

           Recommendations
          

            Trusted by engineers and leaders.
          

        

        

          
          

            

              

                "Sachin operates at the rare intersection of deep systems
                expertise and product-grade pragmatism. He fixes things
                most engineers don't even see."
              

              

                Niranjan Kumar Pandey
                Engineering Manager · Microsoft
              

            

            

              

                "If your AI infra is on fire, you want him on the call.
                Calm, surgical and absurdly fast at root-cause analysis."
              

              

                Don Chichi
                Principal Engineer · Hyperscale Cloud
              

            

            

              

                "He architected our platform's hardest piece — the kind of
                system most people are scared to touch — and made it boring
                to operate."
              

              

                Staff Engineer
                IBM ISL
              

            

            

              

                "Sharp, generous with knowledge, and the only mentor who
                made distributed systems click for me."
              

              

                Senior SDE
                FAANG
              

            

          

          
          

        

      


      
      

        

          
           Let's Build
          

            Ready to accelerate your systems?
          

          

            Whether you need a single architecture review or a long-term
            advisory engagement — let's talk.
          


          

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