Application Support Engineer

Accenture

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Mumbai, Maharashtra0 – 3 Years1 day ago

RoleApplication Support Engineer (AI & GenAI Focus)

LocationMumbai, Maharashtra

Experience0 – 3 Years

QualificationB.E / B.Tech / M.Tech (CS, AI, Data Science)

Job Description

As an Application Support Engineer at Accenture under the Accenture Recruitment 2026 drive, you will act as a software detective, identifying and solving issues within complex business systems. However, this isn’t a traditional support role—you will be deeply involved in Full Stack AI development. You will design and build RAG-based applications, manage LLM inferencing pipelines, and develop scalable microservices using NestJS and Python.
The ideal candidate possesses an experimental mindset, capable of rapidly prototyping solutions in unknown problem spaces. Whether you are troubleshooting a critical system component or experimenting with emerging protocols like the Model Context Protocol (MCP), your work will ensure that Accenture’s AI-driven systems remain production-grade and defect-free.

Design and develop Generative AI applications using frameworks like LangChain and LangGraph.
Build and maintain RAG (Retrieval Augmented Generation) pipelines for enterprise knowledge systems.
Identify, troubleshoot, and solve technical issues within critical business components as a “software detective.”
Develop scalable microservices using NestJS and Python with secure REST API practices.
Implement LLM inferencing pipelines and vector search pipelines for document ingestion.
Experiment with emerging AI standards and multi-agent orchestration patterns.
Collaborate with cross-functional teams to translate functional requirements into technical architecture.
Maintain clear documentation and contribute to MLOps/LLMOps practices.

Education: B.E / B.Tech / M.Tech in Computer Science, AI, Data Science, or related fields (15 years full-time education).
Experience: 0–3 years overall; specifically seeking candidates with exposure to Java Full Stack Development and Python.
AI Core: Hands-on experience with LLMs, prompt engineering, semantic search, and embedding models.
Frameworks: Implementation experience in RAG, Agentic AI (LangChain/LangGraph), or Vector search.
Programming: Strong proficiency in Python; knowledge of NestJS and DevOps is a plus.
Soft Skills: Strong analytical skills, innovation mindset, and the ability to learn new frameworks rapidly.

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