We are seeking an experienced Agentic AI Architect / Senior Full Stack Engineer with 10+ years of software engineering experience and strong hands-on expertise in Agentic AI, Java, Spring Boot, React, Python, LangGraph, RAG, and cloud-native application development. The ideal candidate will have experience delivering large-scale enterprise solutions and working across frontend, backend, AI agent services, and distributed systems.
This role requires strong architecture and development skills, with the ability to design and implement production-ready agentic applications, evaluate AI and RAG performance, and collaborate with engineering, architecture, SRE, and business teams. Experience in telecom, enterprise marketing platforms, or large-scale customer-facing applications is highly desirable.
Roles & Responsibilities:
- Design and develop agentic AI solutions using Python, FastAPI, LangChain/LangGraph, LLMs, conversational workflows, intelligent intake, content generation, and multi-step agent orchestration.
- Lead end-to-end application architecture and development across React-based frontend applications, Java/Spring Boot microservices, REST APIs, Python AI services, and cloud-native components.
- Build and optimize RAG solutions using Google Cloud Platform, Oracle RDS, and PostgreSQL, including embeddings, hybrid search, retrieval pipelines, grounding strategies, and validation of retrieval and generated responses.
- Develop scalable distributed systems using microservices, Kafka, event-driven architecture, BFF patterns, asynchronous processing, parallel API integrations, Docker, and Kubernetes/Helm deployments.
- Establish AI quality and performance validation practices by monitoring latency, token usage, retrieval quality, response accuracy, output consistency, regression, and differences between non-production and production environments.
- Drive architecture, technical design, and production delivery by developing POCs, coordinating cross-repository changes, implementing feature flags and safe rollout strategies, and partnering with SRE, platform, and distributed engineering teams.
- Collaborate with business stakeholders and enterprise application teams to translate requirements into scalable solutions, resolve technical dependencies, improve runtime performance, and deliver incremental production-ready capabilities in a complex enterprise environment.
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