Tech Lead – Full Stack (AI-First Mindset)

Codvo.ai; Pune District; Hybrid; INR 2,000,000 - 3,000,000; Full time

Job summary

A technology firm in India is looking for a Tech Lead with a focus on full-stack development and an AI-first mindset. The role involves leading engineering teams, driving architectural decisions, and integrating AI-driven capabilities into applications. Candidates should have 7–12+ years of experience, strong expertise in React.js, Angular, Node.js, and proven leadership skills. This hands-on position requires mentoring of engineers and contributions to technical best practices while ensuring project delivery on time.

Qualifications

• 7–12+ years of software development experience with strong full‑stack expertise.
• Deep hands‑on skills in React.js, Angular, Node.js, Express.js, and NestJS.
• Strong understanding of microservices, API design, and distributed systems.

Responsibilities

• Lead technical design, architecture decisions, and development workflows across frontend and backend systems.
• Provide direction on frameworks, patterns, code quality, and performance optimization.
• Mentor engineers, perform code reviews, and ensure engineering best practices.

Skills

React.js

Angular

Node.js

Express.js

NestJS

Microservices

API design

AI tools

DevOps

Job description

Job Description: Tech Lead – Full Stack (AI-First Mindset)

Location: [Hybrid/Remote – India]

Experience: 7–12+ years

Role Type: Full-time

About the Role

As a Tech Lead (AI-First), you will lead technical execution across full‑stack applications while actively contributing to architecture, coding, and delivery. You will guide engineers, drive best practices, and integrate AI‑driven capabilities across the development lifecycle—from automation to smart features inside the product. This role is 80% hands‑on, with strong leadership responsibility.

Key Responsibilities

Technical Leadership

• Lead technical design, architecture decisions, and development workflows across frontend and backend systems.
• Provide direction on frameworks, patterns, code quality, and performance optimization.
• Mentor engineers, perform code reviews, and ensure engineering best practices.
• Evaluate new AI tools, frameworks, and libraries for integration into the project.

AI-First Engineering

• Apply AI tools and LLMs to improve developer productivity (code generation, testing, documentation, automation).
• Design systems that can support future AI/ML capabilities (API orchestration, extensible data models, scalable services).
• Partner with AI/ML engineers to embed models into full‑stack applications.

Full‑Stack Development (Hands‑On)

• Build scalable applications using:
  • Frontend: React.js, Angular
  • Backend: Node.js, Express.js, NestJS
• Design and develop RESTful APIs, microservices, and backend logic.
• Build reusable UI components, dashboards, and interactive interfaces.
• Implement secure, optimized, and maintainable code across the stack.

Architecture & System Design

• Contribute to high‑level architecture: microservices, API gateways, event‑driven systems, and cloud‑native design.
• Ensure scalability, reliability, security, and performance benchmarks are met.
• Work with DevOps to strengthen CI/CD pipelines and automation.

Collaboration & Delivery

• Work closely with Product Managers, Designers, DevOps, QA, and AI teams to build robust product increments.
• Break down engineering tasks, provide estimates, and ensure predictable delivery.
• Communicate technical decisions, risks, and timelines clearly to stakeholders.

Qualifications

Must Have

• 7–12+ years of software development experience with strong full‑stack expertise.
• Deep hands‑on skills in:
  • React.js
  • Angular
  • Node.js
  • Express.js
  • NestJS
• Strong understanding of microservices, API design, and distributed systems.
• Proven experience leading technical projects or small teams.
• Experience integrating AI/LLM‑based features OR willingness + capability to adopt AI‑first tools.

Good to Have

• Experience with TypeScript, RxJS, and modern frontend architecture.
• Familiarity with cloud platforms (AWS/Azure/GCP).
• Experience with vector DBs, LangChain, or integrating AI APIs.
• Knowledge of DevOps practices and containerization (Docker, Kubernetes).