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The Full Stack Engineer (AI & Agentic AI Systems) is a strategic professional who will play a pivotal role in architecting and delivering next‑generation intelligent applications that blend advanced software engineering, autonomous agents, and robust end‑to‑end engineering. In this role, you will work across the entire technology stack— REACT based front ends, designing scalable backend services (JAVA/Python/APIs), intuitive user experiences, and AI‑driven workflows that reason, plan, and act with minimal human intervention. You’ll collaborate with cross‑functional teams to transform complex business challenges into innovative, production‑ready AI systems that push the boundaries of automation, intelligence, and modern software engineering.
Job Responsibility:
Design and deliver end‑to‑end solutions spanning architecture, system design, low‑level design, and high‑quality coding across modern full‑stack environments
Engineer AI‑powered features leveraging Google Gemini LLM, Vertex AI, Google ADK, vector databases, A2A protocol, RAG pipelines, MCP, (Model Context Protocol) context engineering, and advanced prompt engineering techniques
Build responsive, modular UI applications using React, integrating complex AI-driven workflows and real‑time interactions
Develop scalable, high‑performance backend services in Java / Python, implementing resilient APIs, event‑driven patterns, and microservices architectures
Implement secure, well‑structured REST and GraphQL APIs, ensuring reliability, versioning discipline, and clean integration patterns across platforms
Optimize system performance and scalability, applying profiling, load‑testing insights, caching strategies, and distributed system tuning
Partner with QE to build and maintain automated test suites (UI, API, integration, and performance), improving release quality and reducing regression risk
Identify, diagnose, and remediate performance bottlenecks, penetration testing vulnerabilities, and production issues with precision and root‑cause clarity
Collaborate cross‑functionally with AI scientists, architects, and product teams to translate business challenges into production‑ready, intelligent agentic systems
Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, with strong fundamentals in algorithms, distributed systems, and software architecture
6–10+ years of full‑stack engineering experience with deep proficiency in React, Java, modern API frameworks, and cloud‑native development
Hands-on experience building AI‑integrated applications using Google Gemini LLM, Vertex AI, ADK, vector databases, RAG pipelines, MCP, and advanced prompt/context engineering
Strong DevOps and automation skills, including CI/CD pipelines, containerization (Docker/Kubernetes), and automated testing across UI, API, and integration layers
Proven ability to design scalable, secure, high‑performance systems, diagnose performance bottlenecks, and address penetration testing findings in production environments