Abhishek Yadav abhiishek340

👨‍💻 About me

I'm a senior software engineer and tech lead who has spent years building and running production systems at established technology companies and fast-moving startups.

At larger companies I learned rigor: high-traffic services, strict reliability targets, security reviews, and codebases that hundreds of engineers depend on. At startups I learned speed: owning a product from a blank repo to paying customers, wearing every hat, and making the call when there is no one else to ask.

Today I bring both together. I lead the architecture of complex products, mentor engineers, and advise multiple AI startups on getting from a promising demo to a reliable, scalable and cost-efficient product.

"Good engineering is invisible. Users just notice that everything works."

🧭 Career arc

timeline
    title From engineer to technical leader
    Foundations     : Full-stack engineering
                    : Web, mobile and data products
    Enterprise      : Large-scale distributed systems
                    : Reliability, security and compliance
                    : Cross-team platform work
    High-growth     : Tech lead on 0 → 1 products
                    : Hiring, mentoring and engineering culture
                    : Cloud cost and performance at scale
    Today           : Senior engineer and tech lead
                    : Advisor to multiple AI startups
                    : LLM products, agents and AI infrastructure

🏢 Enterprise

Designed services under strict SLAs and heavy traffic
Led legacy-to-cloud migrations without downtime
Ran architecture and security reviews across teams
Built CI/CD and observability shared by many teams

🚀 Startups

Took products from idea to launch as the founding engineer
Set up the stack, infrastructure and delivery process from day one
Hired and mentored early engineering teams
Balanced speed with sustainability under real deadlines

🤖 AI advisory

Advised multiple AI startups on architecture and roadmap
Designed RAG, agent and voice pipelines
Built evaluation and guardrail strategies for LLM output
Cut inference cost and latency with caching and model routing

🧠 Areas of expertise

mindmap
  root((Abhishek))
    Architecture
      Distributed systems
      Microservices and event-driven design
      API and data modelling
      Scalability and performance
    Applied AI
      LLM integration
      RAG and vector search
      AI agents and tool use
      Evaluation and guardrails
      Voice interfaces
    Cloud and DevOps
      AWS and GCP
      Docker and Kubernetes
      Infrastructure as code
      CI/CD and observability
    Product engineering
      React and Next.js
      Node.js and Java
      Mobile with Kotlin
      Web3 and smart contracts
    Leadership
      Technical strategy
      Mentoring and hiring
      Startup advisory
      Engineering culture

🛠️ Tech arsenal

Languages
Frontend
Backend
Data
Cloud & DevOps
AI / ML

🤝 Startup advisory

I partner with founders and early engineering teams building AI-first products.

Stage	How I help
💡 Idea → prototype	Validate technical feasibility, choose the stack and models, and scope an MVP that can grow
🧪 Prototype → product	Harden the demo with tests, CI/CD, monitoring, auth and a sensible cloud footprint
📈 Product → scale	Fix performance bottlenecks, control inference spend, and design for 10× traffic
👥 Team building	Interview loops, onboarding, code review culture and engineering rituals that scale

⚙️ How I build

flowchart LR
    A(["🎯 Problem"]) --> B["📝 Design doc<br/>& trade-offs"]
    B --> C["🧪 Typed code<br/>& tests"]
    C --> D["🤖 CI + preview<br/>environments"]
    D --> E["🚦 Feature-flagged<br/>release"]
    E --> F["📊 Observe<br/>& iterate"]
    F -.-> A

Principle	In practice
Design before code	Written proposals, explicit trade-offs, decisions captured as ADRs
Make the safe path the easy path	Typed interfaces, automated tests, preview environments, feature flags
Own it in production	Dashboards, alerts and runbooks ship with the feature
Multiply the team	Thoughtful code reviews, pairing, mentoring and clear documentation

🔭 Currently

🏗️ Leading architecture for AI-native products: agents, retrieval and voice
🤝 Advising AI startups on scaling their platforms and engineering teams
📚 Going deeper on LLM evaluation, AI infrastructure and event-driven systems
💼 Open to senior / staff engineering roles, advisory and technical partnerships

Off the clock: 📸 photography · 🏀 basketball (1v1 challenge always open)

Building something ambitious with AI? Let's talk.

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