Looking for a strong, hands-on Team Lead for Full-Stack Development to step into a senior leadership position on our engineering team. We need someone who can take ownership from day one, ramp up fast, and keep our platform shipping without missing a beat.

Our platform is scaling fast with a target of 100% year-on-year growth. The platform that carries that ambition - search, catalogue, checkout, order management, fulfillment, and support - has to get faster, smarter, and more reliable at every traffic peak. We are not adding headcount to do more of the same; we are hiring leaders who use AI to change the slope of what a team can ship.

As Team Lead, you will run development in a controlled, secure environment, drive faster deployment turnaround, and co-own the modules aligned to you alongside our other team leads. You will be jointly responsible for keeping the system up and running with effectively 100% uptime. You will work across our Next.js / React frontend, Node-based services, MongoDB and Redis data layer, and AWS infrastructure - agentic by default, human in command.

What "AI-Native" Means Here

- You work AI-native
- Agentic coding as the baseline. You drive AI coding agents (Claude Code, Cursor, Copilot-class tools) to scaffold, implement, refactor, and migrate - reviewing and steering output rather than typing every line. You know when to delegate to an agent and when to take the keyboard back.
- AI-assisted review and testing. You use AI to generate test coverage, catch regressions, draft documentation, and pre-review your own PRs before a human sees them - quality goes up because the cheap checks are automated.
- Spec-first, prompt-literate. You can decompose a fuzzy business ask into a crisp spec an agent can execute against, and you write prompts and context the way you'd write good interfaces - precisely.
- Velocity with judgment. AI multiplies output, so the bottleneck moves to taste and verification. You are accountable for everything that ships, agent-generated or not - no "the AI wrote it" excuses.
- You build AI into the product
- Intelligent commerce surfaces. LLM- and ML-powered features in the real customer path - semantic and natural-language product search, recommendations, smart cart and substitution, catalogue content generation.
- Support and ops automation. Retrieval-augmented assistants for customer support, agent-assist for the ops team, automated query resolution, and intelligent routing.
- Decision intelligence. Turning operational and transactional data into models and pipelines that drive merchandising, pricing signals, demand forecasting, and fraud/anomaly detection.
- Production-grade AI. Evals, guardrails, latency and cost control, observability, and graceful fallback - AI that survives contact with real traffic, not a demo.

Key Responsibilities

- Team leadership: lead a team of full-stack engineers, set the standard for AI-native delivery, review code with a teaching voice, and mentor developers while staying deeply hands-on.
- Module co-ownership: co-own the modules aligned to you alongside other team leads, taking shared accountability for their quality, delivery, scalability, and tech-debt management.
- Controlled & secure development: manage development in a controlled, well-governed workplace with secure-by-default practices, code reviews, access control, and protected branches.
- Faster deployment turnaround: streamline CI/CD to deliver rapid,



reliable releases with safe rollbacks and minimal risk.
- Infrastructure & uptime: help manage the AWS infrastructure and be jointly responsible for keeping the system up and running, targeting effectively 100% uptime through monitoring, alerting, and fast incident response.
- End-to-end delivery: take features from ambiguous business problem to shipped, monitored production capability - frontend, backend, and the AI layer in between.
- Architecture & scalability: own architecture and design decisions for your surface area on AWS, ensuring reliability and performance under real commerce traffic and seasonal peaks.
- Engineering quality: hold a high bar on code review culture, test coverage, observability, and incident response - and use AI to make that bar cheaper to maintain, not lower.
- Collaboration & influence: partner directly with product, operations, and leadership to translate growth goals into technical execution; bring options and trade-offs, not just problems.

Required Skills - Core Stack

- Next.js - expert-level command of the framework including the App Router and Pages Router, Server Components, SSR, SSG, ISR, middleware, API routes, image optimization, and Core Web Vitals tuning.
- React - deep expertise in modern React - functional components, hooks, context, state management (Redux / Zustand / React Query or similar), memoization, code-splitting, lazy loading, and reusable, scalable component architectures.
- JavaScript & TypeScript - strong fundamentals in modern ES (ES6+), asynchronous programming, and type-safe development across frontend and backend.
- Node.js - building high-performance backend services with Node.js and frameworks such as Express / NestJS / Fastify, including event loop and concurrency understanding.
- API design - designing, building, versioning, and documenting robust REST and GraphQL APIs; authentication tokens (JWT / OAuth), rate limiting, pagination, and webhooks; microservices.
- MongoDB - data modeling and schema design, indexing strategy, the aggregation framework, transactions, replica sets, sharding, and query profiling/optimization for scale.
- Redis - caching strategies, session storage, pub/sub, distributed locks, rate limiting, and queues; cache invalidation and TTL management.
- AWS architecture - designing scalable, resilient cloud architecture across EC2, S3, Lambda, API Gateway, CloudFront (CDN), Route 53, ELB/ALB, VPC, IAM, RDS, ECS, SQS/SNS, and CloudWatch.
- AI / ML - practical experience integrating AI/ML into production - LLM / RAG, semantic and natural-language search, recommendations, embeddings / vector stores, evals, guardrails, latency and cost control; Python a strong plus.
- Mobile (plus) - React Native exposure for shared frontend delivery is a bonus.
- Frontend foundations - solid HTML5, CSS3, responsive design, Tailwind / styled-components, accessibility, and cross-browser compatibility.

Required Skills - Engineering Practices

- Version control (Git) - advanced Git workflows - branching strategies (GitFlow / trunk-based), pull requests,



code reviews, conflict resolution, protected branches, and clean commit hygiene.
- CI/CD - building and maintaining automated build, test, and deployment pipelines (GitHub Actions / GitLab CI / Jenkins / AWS CodePipeline) for fast, reliable releases.
- Deployment & releases - blue-green and canary deployments, zero-downtime rollouts, feature flags, automated rollbacks, and release management for faster turnaround.
- Serverless & event-driven - AWS Lambda, API Gateway, and event-driven architecture using queues and pub/sub for decoupled, scalable systems.
- Containerization & IaC - Docker (and ideally Kubernetes / ECS) for consistent environments, plus infrastructure-as-code with Terraform / CloudFormation.
- Code quality & testing - linting (ESLint/Prettier), design patterns, clean code, refactoring; unit, integration, and end-to-end testing (Jest / Cypress / Playwright), with AI-assisted coverage.
- Code optimization & performance - profiling and tuning frontend and backend performance, bundle size, database queries, caching layers, and API latency; improving Core Web Vitals.
- Code security - secure-by-default coding, OWASP Top 10 awareness, authentication/authorization, secrets management, dependency/vulnerability scanning, and data protection.
- Monitoring & observability - logging, metrics, alerting, and tracing (CloudWatch / Grafana / Sentry / Datadog or similar) for reliability and fast incident response toward near-100% uptime.
- AI-native workflow - fluency with agentic coding tools (Claude Code, Cursor, Copilot-class), spec-first prompting, AI-assisted review/testing, and production AI practices (evals, guardrails).
- SEO & discoverability - Google Search Console, technical SEO, structured data, sitemaps, and performance for organic visibility.
- Scalability & reliability - designing for high traffic, load balancing, auto-scaling, fault tolerance, backups, and disaster recovery.
- Agile delivery - working in Agile/Scrum, sprint planning, estimation, on-call participation, root-cause discipline, and collaborative delivery with product and design.

Must-Have

- 6+ years building and scaling production software - you've shipped, owned, and operated real systems, with team-leading experience.
- Demonstrated AI-native workflow: you already build with coding agents daily and can show how it changes your output and quality.
- Strong full-stack proficiency - production depth in Next.js / React and Node.js; comfort across the stack.
- Sound system-design and architecture judgment under real traffic and constraints.
- Hands-on experience integrating LLMs or ML into real applications - prompts, context, evals, latency, and cost as engineering concerns.
- Exceptional problem-solving and the judgment to make sound technical decisions quickly.
- A bias for clean delivery - code quality, testing, documentation - balanced with shipping speed.
- Explicit communicator who owns outcomes end to end and can operate with founders and engineers alike.
- Available to join on an immediate basis.

Nice-to-Have

- E-commerce, marketplace, or high-traffic consumer-platform experience.
- Python and data-engineering / MLOps exposure.
- Experience taking an AI feature from prototype to production at scale, with real evals and guardrails.
- Exposure to Docker / Kubernetes and infrastructure-as-code.
- Open-source contributions or a public body of AI-native work.

📌 Team Lead - Full Stack Development (India)
🏢 Gostravvy
📍 India