15 hours ago
Kochi, IndiaStaff+
Responsibilities
- Design, develop, and support production-grade full-stack AI applications on GCP across frontend, backend, APIs, data integration, AI services, and cloud deployment.
- Integrate Vertex AI, Gemini models, Generative AI APIs, embeddings, RAG pipelines, semantic search, and other AI/ML capabilities into enterprise applications.
- Build responsive frontend applications and scalable backend services, REST APIs, microservices, event-driven components, and enterprise integrations.
- Implement AI-enabled features including conversational interfaces, enterprise search, knowledge assistants, recommendations, summarization, information extraction, document processing, and content generation.
- Design data persistence and integrations using relational databases, NoSQL databases, vector databases, document repositories, third-party services, and enterprise systems.
- Develop cloud-native solutions using GCP compute, storage, messaging, API management, identity, security, and secrets-management services.
- Implement RAG architectures involving document ingestion, chunking, embeddings, vector search, metadata filtering, prompt engineering, and knowledge retrieval.
- Implement authentication, authorization, API security, identity management, access control, encryption, secrets management, and secure software development practices.
- Optimize frontend, backend, API, model, token, caching, scalability, and cloud-cost performance.
- Build automated testing and CI/CD pipelines covering application builds, testing, containerization, security validation, infrastructure deployment, and production releases.
- Implement logging, monitoring, tracing, alerting, dashboards, health checks, and production observability.
- Troubleshoot issues across UI components, APIs, backend services, AI integrations, databases, containers, networking, authentication flows, cloud infrastructure, and deployments.
- Provide technical guidance, conduct code and design reviews, mentor junior engineers, and contribute to engineering standards and best practices.
- Collaborate with solution architects, AI engineers, data engineers, UX designers, DevOps engineers, security teams, product owners, and business stakeholders.
Requirements
- At least 8 years of professional software engineering experience, with strong full-stack, backend, cloud-native, and enterprise integration experience.
- B.Tech, BE, M.Tech, or MCA qualification.
- Strong hands-on experience developing and deploying solutions on Google Cloud Platform, particularly Vertex AI, Cloud Run, GKE, Cloud Functions, Pub/Sub, BigQuery, Cloud Storage, Cloud SQL, Firestore, IAM, Secret Manager, Cloud Logging, and Cloud Monitoring.
- At least 2 years of the required experience involving AI or Generative AI, including LLMs, Vertex AI, Gemini models, intelligent search, or related capabilities.
- Strong frontend experience with React, Angular, Next.js, TypeScript, JavaScript, HTML, and CSS or equivalent technologies.
- Strong backend programming experience with Python, Java, Node.js, or TypeScript and frameworks such as FastAPI, Flask, Django, Spring Boot, Express.js, or NestJS.
- Experience designing REST APIs, microservices, event-driven applications, asynchronous processing, distributed architectures, and enterprise integration services.
- Understanding of RAG, embeddings, vector search, semantic search, document ingestion, chunking, prompt engineering, grounding, context management, structured outputs, function/tool calling, guardrails, and AI application error handling.
- Experience with vector and search technologies such as Vertex AI Vector Search, AlloyDB AI, Elasticsearch, OpenSearch, Pinecone, Weaviate, pgvector, or equivalent.
- Experience with BigQuery, Cloud SQL, AlloyDB, PostgreSQL, MySQL, Firestore, MongoDB, or equivalent relational and NoSQL databases.
- Experience with Docker, Kubernetes, GKE, serverless technologies, Cloud Run, and cloud-native architecture patterns.
- Experience with Pub/Sub, Kafka, messaging platforms, event queues, and background workers.
- Knowledge of OAuth 2.0, OpenID Connect, JWT, Google Cloud IAM, service accounts, API security, and role-based access control.
- Experience with Git-based development, code reviews, automated testing, CI/CD, Cloud Build, GitHub Actions, GitLab CI, Jenkins, or equivalent technologies.
- Experience with Terraform, Google Cloud Deployment Manager, or equivalent Infrastructure as Code tools is desirable.
- Experience with AWS or Microsoft Azure AI and cloud services is an advantage.
- Experience with LangChain, LangGraph, LlamaIndex, Google Agent Development Kit, MCP, A2A, or equivalent AI application and workflow technologies is desirable.
- Strong system-design, troubleshooting, analytical, communication, mentoring, technical leadership, and stakeholder-collaboration skills.
Tech Stack
AngularApache KafkaCSSDjangoDockerElasticsearchExpressFastAPIFlaskGitHub ActionsGitLab CI/CDGoogle BigQueryGoogle Cloud PlatformHTMLJavaJavaScriptJenkinsKubernetesMongoDBMySQLNestJSNext.jsNode.jsPostgreSQLPythonReactSpring BootTerraformTypeScript
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.