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Pranay Mohite

Staff Engineer | AI-focused Product Architect | DevOps Leader | Fractional CTO

Positioning

I operate at the intersection of product engineering, SaaS architecture, platform/DevOps execution, and pragmatic AI adoption. I’ve spent 18+ years building and running production systems—now as a Founder & Product Architect at BuzzNeuron, and previously in senior roles across enterprise teams.

I am comfortable setting technical direction with founders and stakeholders, and also going deep into systems: boundaries, data flows, reliability, cost drivers, and the code that ships. My goal is simple: reduce delivery risk and make engineering decisions that improve real business outcomes.

Location
India · Remote · Global
Experience
18+ Years

I Help Organizations

Clear senior-level engagements for founders, product leaders, and engineering teams who want strong architecture, reliable delivery, and measurable outcomes.

  • 01

    Architect and evolve multi-tenant SaaS platforms

    Define boundaries, data flow, and scalability patterns (modular monolith or microservices) so the product can grow without brittle coupling.

  • 02

    Stabilise, modernise, or rescue production systems

    Reduce incident frequency, improve performance, and de-risk migrations with a focused plan across code, infrastructure, and operations.

  • 03

    Build platform/DevOps foundations that unblock delivery

    Practical CI/CD, containerised deployments, environment strategy, and operational runbooks that make releases repeatable and safe.

  • 04

    Turn business goals into an executable technology roadmap

    Translate strategy into architecture decisions, milestones, and a delivery plan your team can execute—without accidental complexity.

  • 05

    Design cost-aware cloud systems (without sacrificing reliability)

    Find the real cost drivers, right-size architecture choices, and introduce sensible async/caching/observability to control spend as usage grows.

  • 06

    Introduce AI capabilities safely and pragmatically

    Add AI where it creates measurable value (workflows, insights, automation) with clear constraints, evaluation, and rollout guardrails.

Services

Clear engagement packages where I take full ownership—designed for founders, product leaders, and teams that want strong architecture, reliable delivery, and measurable outcomes.

Production Architecture Support

Practical architecture help for systems already running in production.

  • Understand your current system and data flow (modules/services, tenancy, reliability, cost drivers)
  • Propose improvements you can implement without disrupting delivery
  • Agree on a clear next-step plan your team can execute
Best for
Teams with scaling pain, rising complexity, or unclear architectural direction

Stabilisation Sprint (Reliability + Delivery)

A focused sprint to make releases calmer and production more predictable—without overhauling everything.

  • Identify recurring incident patterns and operational gaps
  • Add basic delivery guardrails (CI/CD checks, release steps, rollback plan)
  • Set a minimal observability baseline (logs/metrics/traces) to speed up debugging
Best for
Teams stuck in firefighting or afraid to ship

Full Stack & Product Engineering

Hands-on building for SaaS products: ship features, improve performance, and keep the codebase maintainable.

  • Build product features end-to-end (Next.js/NestJS/.NET, APIs, background jobs)
  • Improve core workflows: performance, reliability, and developer experience
  • Make architecture improvements while continuing delivery (no “big rewrite”)
Best for
Teams that need senior hands-on engineering to ship and keep quality high

AI / Data-Driven Systems (Practical Adoption)

Add AI and data-driven capabilities where they make sense—kept practical, testable, and safe to run in production.

  • Identify 1–2 high-value use-cases (automation, insights, assistance) tied to workflows
  • Design the data flow + integration (storage, APIs, evaluation, rollout)
  • Build a small working slice and iterate based on results
Best for
Product teams that want to add AI without turning the product into a research project

Platform / DevOps Foundations

Practical improvements to how you build, deploy, and operate your product—focused on repeatability and stability.

  • Containerisation and deployment flow (Docker/Kubernetes where it fits)
  • CI/CD improvements and release steps that reduce mistakes
  • Operational basics: secrets, environments, runbooks, and ownership
Best for
Teams that ship slowly due to fragile deployments or unclear ops practices

Typical Engagements

Depending on what you need, I can plug in as a senior individual contributor, a hands-on architect, or a lightweight engineering leader. In practice, engagements often span more than one of these at the same time.

How I engage

  • Engineer
  • Senior Engineer
  • Tech Lead
  • Staff / Principal Engineer
  • Solutions / Product Architect
  • Engineering Manager
  • Head of Engineering
  • Director of Engineering
  • Fractional CTO

Technology Stack

A snapshot of tools I’ve used to build and run production systems across SaaS, cloud, and DevOps (kept intentionally practical, not a “laundry list”).

Languages

  • TypeScript
  • JavaScript
  • C#
  • Bash / PowerShell

Frontend

  • Next.js (React)
  • Angular
  • Redux

Backend

  • NestJS
  • .NET Core
  • REST APIs
  • GraphQL (when it fits)

Data & Async

  • PostgreSQL
  • MS SQL Server
  • MongoDB
  • Redis
  • Prisma
  • Entity Framework
  • BullMQ

Architecture & Delivery

  • Multi-tenant SaaS
  • Microservices
  • Modular Monolith
  • Event-driven systems
  • Nx monorepo
  • ADR

Cloud, Platform & DevOps

  • AWS
  • Azure
  • Kubernetes
  • Docker
  • CI/CD
  • GitHub Actions
  • Serverless (Lambda/EventBridge)
  • S3

Security & Observability

  • OAuth2
  • OpenID Connect
  • RBAC
  • OpenTelemetry
  • Application Insights

Search & Indexing

  • Elasticsearch

Artificial Intelligence

  • OpenAI API
  • Gemini
  • LangChain
  • LlamaIndex
  • n8n
  • MCP
  • RAG
  • Context Engineering
  • Prompt Engineering
  • ML Algorithms

Networking / Connectivity

  • WireGuard
  • Tailscale
  • Headscale

Tooling

  • Electron
  • Coolify

Discuss Your Product

Share your goals and current challenges. I will respond with a practical engagement path.