Job Title – Senior Lead Full Stack AI Engineer – Associate Manager - ACS SONG

Management Level: Level 8 – Associate Manager
Location: Kochi, Coimbatore, Trivandrum
Must have skills: Full Stack Application Development, GCP, Generative AI
Good to have skills: Model Context Protocol (MCP)/ Agent2Agent (A2A)
Experience: 8 - 12 years of experience is required

Educational Qualification: B. Tech/BE/M. Tech/MCA

Job Summary

We are seeking a Senior Lead AI Full Stack Engineer specializing in Google Cloud Platform (GCP) with 8+ years of professional software engineering experience and strong expertise in building modern, cloud-native, AI-enabled applications. The ideal candidate should have hands-on experience across frontend development, backend services, APIs, microservices, databases, cloud infrastructure, and AI/Generative AI integration (at least 2 years of the total years of experience), with GCP as the primary technology platform.

The role will focus on designing and developing end-to-end applications that integrate AI capabilities such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent search, conversational interfaces, and AI-powered business workflows.

The candidate will work closely with solution architects, AI engineers, data engineers, UX teams, product owners, and Dev Ops teams to deliver scalable, secure, high-performing, and production-ready AI applications.

Roles and Responsibilities

- Design, develop, and support production-grade full-stack AI applications on GCP, covering frontend interfaces, backend services, APIs, data integration, AI services, and cloud deployment.
- Integrate Vertex AI, Gemini models, Generative AI services, RAG solutions, intelligent search,



and AI/ML capabilities into enterprise web and digital applications.
- Build scalable frontend and backend components using modern frameworks and cloud-native architecture patterns while ensuring performance, security, maintainability, and usability.
- Leverage GCP services and Dev Ops practices to deliver highly available, observable, secure, and automated AI applications across development, testing, and production environments.
- Design, develop, and maintain end-to-end AI-enabled web applications and enterprise solutions on Google Cloud Platform.
- Develop responsive and user-friendly frontend applications using contemporary frameworks such as React, Angular, Next.js, or equivalent technologies.
- Develop scalable backend services, REST APIs, microservices, and integration layers using technologies such as Python, Java, Node.js, FastAPI, Spring Boot, or equivalent frameworks.
- Integrate applications with Vertex AI, Gemini models, Generative AI APIs, embeddings, RAG pipelines, semantic search, and other AI/ML services available within GCP.
- Design and implement conversational AI, enterprise search, recommendation, summarization, document-processing, and other AI-powered application capabilities.
- Build integrations between AI applications and enterprise systems, databases, APIs, document repositories, third-party services, and internal applications.




- Design and implement data persistence using technologies such as Big Query, Cloud SQL, AlloyDB, Firestore, Cloud Storage, Memorystore, or other suitable databases and storage services.
- Develop cloud-native solutions using GCP services such as Cloud Run, Google Kubernetes Engine (GKE), Cloud Functions, Pub/Sub, API Gateway, Apigee, Cloud Storage, and Secret Manager.
- Implement Retrieval-Augmented Generation solutions using document ingestion, chunking, embeddings, vector search, metadata filtering, prompt engineering, and knowledge retrieval patterns.
- Implement secure authentication, authorization, API security, identity management, secrets management, and access control using Google Cloud IAM, Identity Platform, OAuth/OIDC, service accounts, and related security services.
- Optimize application and AI solution performance, including frontend responsiveness, backend latency, API performance, model response time, token usage, caching, scalability, and cloud cost.
- Implement automated testing across frontend, backend, APIs, integrations, and AI components using appropriate unit, integration, functional, and end-to-end testing frameworks.
- Debug and resolve issues across UI components, APIs, backend services, AI integrations, databases, cloud infrastructure, authentication flows, network connectivity, and production deployments.
- Implement logging, monitoring, tracing, alerting, and observability using Google Cloud Logging, Cloud Monitoring, Cloud Trace, Open Telemetry, or equivalent technologies.
- Collaborate with architects, AI engineers, data engineers, product owners, UX designers, security teams, and Dev Ops engineers while following software engineering, architecture, security, and coding best practices.

📌 Senior Lead Full Stack AI Engineer (Kochi)
🏢 Accenture
📍 Kochi