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Teach and research data engineering, database systems, and AI-ready infrastructure at a top Australian university, building scalable systems and mentoring students.
Lead red-team operations to simulate advanced cyberattacks, uncover vulnerabilities, and improve Sun Life’s defenses through penetration testing, exploit development, and adversary emulation.
Lead the Mobile Apps Sub-domain (Android and iOS teams) for M&S's retail app, driving technical excellence, team development, and customer-facing solutions using modern mobile frameworks like Swift, Kotlin, and testing tools.
Lead a team building low-latency Java payment systems using Spring Boot, Kafka, and gRPC, ensuring secure, high-performance code and scalable distributed architectures.
Build and maintain a shared frontend platform in React/TypeScript, AWS services, and CI/CD pipelines that power Cisco’s security products and microapps.
Build and optimize GPU kernels and inference frameworks (e.g., vLLM) to accelerate large language model serving, integrating research into production-grade, open-source software.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, then integrate them into enterprise systems with clean, testable code and CI/CD.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases; implement tools, prompts, and CI/CD while integrating enterprise APIs and ensuring safety.
Builds AI-native applications by implementing LLM tooling, RAG pipelines, and vector search; integrates AI into enterprise systems with Python/TypeScript/Java, frameworks like LangChain, and vector DBs (pgvector, Pinecone).
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases, integrating enterprise APIs and ensuring robust testing and safety. Core stack includes Python, TypeScript/Node.js, and Java with frameworks like LangChain and Spring Boot.
Build agentic AI applications using LLMs, RAG pipelines, and vector search; implement tools, prompts, and CI/CD while integrating enterprise APIs and data sources.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector databases. Develop, test, and integrate agents with enterprise APIs and cloud services.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases. Develop agents, prompts, and integrations with clean code and CI/CD in Python, Java, or TypeScript.
Custom Software Engineer at Accenture in Chennai builds agentic AI applications using LLM tooling, RAG pipelines, vector search, and API integrations, with core techs including Java Full Stack, Python, TypeScript/Node.js, and vector DBs.
Build agentic AI applications using LLMs, RAG pipelines, and vector search, integrating enterprise APIs and data sources into production systems.
Build AI-powered applications using LLMs, RAG pipelines, and vector search, integrating APIs and enterprise systems while owning full-stack development from prototype to production.
Build AI-powered agentic applications by implementing LLM tooling, RAG pipelines, and vector search; integrate with enterprise systems while ensuring scalability, safety, and rapid iteration.
Build AI-powered agentic applications using LLMs, RAG pipelines, and vector search, integrating enterprise APIs and ensuring robust, testable code and CI/CD.
Build AI-powered applications using LLMs, RAG pipelines, and vector databases; implement agents, prompts, and evaluation loops while integrating enterprise APIs and ensuring robust CI/CD.
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