Senior - AI driven Full Stack Developer Fint Solutions

8.0 - 13.0 years

15 - 30 Lacs

hyderabad

Hybrid

Only Hyderabad candidates who can join in less than 15day or immediate need to apply Key Skills & Requirements: 1. Full-Stack Web Development Core Technologies: JavaScript/TypeScript - Advanced proficiency with ES6+, async/await patterns Node.js - Server-side development, API design, microservices architecture React/Vue.js - Modern component-based frontend development with hooks, state management HTML5/CSS3 - Semantic markup, responsive design, CSS Grid/Flexbox Web Server Management - Nginx configuration, reverse proxy setup, SSL/TLS Enterprise Requirements: Experience with enterprise-scale applications Microservices architecture GraphQL implementation and schema design 2. AWS Serverless Architecture (Must-Have) Core AWS Services: AWS Lambda - Function design, cold start optimization, event-driven architecture API Gateway - REST/GraphQL APIs, request validation, throttling S3 - Object storage, static hosting, data lakes, event triggers DynamoDB - NoSQL design patterns, GSI/LSI optimization CloudFormation/CDK - Infrastructure as Code Advanced AWS: Amazon Bedrock - LLM integration, model selection, prompt optimization (Highly Preferred) EventBridge - Event-driven workflows, service decoupling Step Functions - Complex workflow orchestration CloudWatch - Monitoring, alerting, custom metrics VPC/Security Groups - Network security, service isolation 3. AI/ML & LLM Integration (Critical) LLM Platforms: OpenAI API - GPT models, function calling, structured outputs Anthropic Claude - API integration, prompt engineering best practices Amazon Bedrock - Multi-model integration, guardrails implementation AI/ML Concepts: Prompt Engineering - Chain-of-thought, few-shot learning, prompt optimization Context Management - Token optimization, conversation state, memory systems Vector Databases - Embedding generation, semantic search, RAG implementation Agent Frameworks - Multi-agent systems, tool integration, workflow orchestration RAG Systems - Retrieval-augmented generation, knowledge base integration Bonus Skills: Fine-tuning - Model customization, training pipeline management MLOps - Model deployment, monitoring, A/B testing 4. Enterprise Integration & Data Database Technologies: SQL - PostgreSQL, MySQL, complex queries, performance optimization NoSQL - MongoDB, DynamoDB, data modeling, scaling patterns Vector Databases - Pinecone, Weaviate, Milvus for AI applications Redis - Caching strategies, session management, pub/sub patterns Integration Patterns: REST/GraphQL APIs - Design, versioning, documentation (OpenAPI/Swagger) Message Queues - SQS, SNS, RabbitMQ for asynchronous processing Event Streaming - Apache Kafka, real-time data processing ETL/ELT - Data pipeline design, transformation logic Preferred Experience: Enterprise AI development and deployment Large-scale system architecture Multi-tenant SaaS applications with enterprise security Real-time AI applications with sub-second response requirements Regulatory compliance experience (SOX, GDPR, SOC2) What You'll Build: AI-powered enterprise applications serving thousands of users Serverless microservices with event-driven architecture Intelligent automation systems integrating LLMs with business processes Developer platforms enabling AI adoption across the organization

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