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Full Stack Engineer

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Onsite

Full Stack Engineer

Central Business Solutions

Full Stack Engineer

Skills

DockerNestReactNodeTypescriptTesting & QAPostgreSQLAWS LambdaKafkaRedisSnowflakeNeo4jGraphQLDatadogPlaywrightAIAWSdbtKubernetesOptimizelySalesforceApache AirflowTerraformAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Delhi, India

Work mode:

Onsite

Published on:

14 October 2026

What they need


Job highlights

  • . Bachelors degree in Computer Science,Engineering,or related field,or equivalent experience
  • . - indicates a required field
  • . Backend experience with Node.js and NestJS building modular,tested services
  • experience with high-autonomy,end-to-end ownership

We're seeking a Full Stack Engineer to build and own features across layered platform - from the member-facing React experience through the GraphQL API layer, into the AI-powered intelligence and data services that drive personalized leadership insights. This is a high-ownership, end-to-end role: you'll take features from concept through production release, instrument them, and iterate on data.

Platform Layers You'll Work Across Experience: React, TypeScript, Optimizely, Apollo GraphQL API Orchestration: Apigee, GraphQL, Auth0, Redis, Kafka Leadership Intelligence (AI): OpenAI, Google Gemini, Neo4j, Snowflake, PostgreSQL, dbt, Airflow Systems of Record: Salesforce, PostgreSQL DevOps Hosting: AWS/Azure, Kubernetes, Terraform, Datadog

What You'll Do

  • Own the full feature lifecycle - architecture, implementation, code review, QA, deployment, and post-launch monitoring.

  • Build responsive React/TypeScript frontends integrated with Optimizely; design Apollo GraphQL schemas and resolvers served through Apigee; build modular Node.js/NestJS backend services using Redis for caching and Kafka for event-driven workflows.

  • Design and query PostgreSQL schemas (TypeORM/Prisma); collaborate on Snowflake pipelines and dbt models feeding the Leadership Intelligence layer.

  • Integrate OpenAI and Google Gemini APIs for AI-powered discovery, recommendations, and matching; work with Neo4j graph data for relationship-driven insights.

  • Use AI-assisted development workflows (pair programming, code generation, test scaffolding) to increase velocity without compromising quality; handle AI feature failures, timeouts, and token costs with a production mindset.

  • Instrument features with PostHog and Datadog; design and run A/B experiments and feature-flag rollouts via Optimizely; use data to drive iteration.

  • Contribute to architecture decisions, ADRs, and post-incident reviews; address performance bottlenecks across the stack (GraphQL resolvers, N+1 queries, frontend rendering, mobile time-to-interactive).

  • Partner with product, design, the Lead Security Engineer, and DevOps to ensure features are secure, well-architected, and operationally sound from the start.

    Required Qualifications - 5-7 years of professional software engineering experience shipping production-grade products end-to-end. Strong TypeScript/React skills (component architecture, state management, hooks, performance). Backend experience with Node.js and NestJS building modular, tested services. - GraphQL experience (schema design, resolvers, subscriptions, Apollo client/server) and familiarity with API gateway patterns (Apigee or equivalent). PostgreSQL proficiency (query optimization, schema design, TypeORM/Prisma). Experience with Auth0 or equivalent identity platforms. - Familiarity with Redis and Kafka (or similar) for caching and event-driven/message-queue patterns.

Nice to Have Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience. - Production experience with OpenAI, Google Gemini, or other LLM APIs (prompt engineering, rate limiting, fallback handling, cost management).

  • Strong architectural thinking and clear technical communication; experience with high-autonomy, end-to-end ownership. Neo4j or other graph database experience. Snowflake/data warehouse experience with dbt or Airflow. Optimizely or similar experimentation / feature-management platforms. Salesforce integration experience. AWS experience (ECS, RDS, Lambda, S3, CloudWatch). Docker, Kubernetes, or Terraform. Testing with Vitest, Jest, or Playwright (unit, integration, e2e). - indicates a required field.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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