Apply on Kit Job: kitjob.in/job/46vtad

Project Role : Application Support Engineer

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Project Role Description : Act as software detectives, provide a dynamic service identifying and solving issues within multiple components of critical business systems.

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Must have skills : Python (Programming Language)

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Good to have skills : AI & Data Solution Architecture, Generative AI

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Minimum 0-2 year(s) of experience is required

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Educational Qualification : 15 years full time education

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Summary

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We are looking for a Full Stack AI & Modern Technology Engineer with strong hands-on experience in Generative AI, Agentic AI frameworks, and modern microservices-based architectures. The candidate will be responsible for designing and building RAG-based AI applications, agentic workflows, and scalable backend systems deployed on cloud platforms.

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The ideal candidate should have strong programming skills, curiosity to experiment with emerging technologies, and the ability to quickly prototype innovative AI solutions.

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Roles & Responsibilities:

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AI/GenAI Development

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Design and develop Generative AI applications using LangChain and LangGraph frameworks.

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Build RAG (Retrieval Augmented Generation) pipelines for enterprise knowledge systems.

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Develop agentic AI workflows and orchestration pipelines using LangGraph.

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Implement LLM inferencing pipelines using open-source or enterprise models.

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Build AI pipelines for document ingestion, embedding, vector search, and response generation.

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Experiment with emerging AI standards and protocols such as MCP (Model Context Protocol).

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Backend & Microservices Development

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Develop scalable microservices using NestJS and Python.

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Design and build REST APIs with secure programming practices.

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Implement event-driven integrations using webhooks and asynchronous messaging patterns.

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Develop DAG-based workflows and data pipelines.

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Data & AI Infrastructure

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Implement vector search and semantic retrieval pipelines using:

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otpgVector/ AWS OpenSearch/ Milvus

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Design and manage metadata stores using PostgreSQL / AWS RDS.

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Work with Apache Spark or distributed data processing frameworks for large-scale data pipelines.

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Cloud & Platform Engineering

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Build and deploy applications on AWS or GCP cloud platforms.

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Implement scalable AI application architectures using:

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otContainerized workloads and working knowledge on dockers/ kubernetes otAWS app services (incl. AWS Bedrock)

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otManaged database services

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Work with cloud-native services for AI model hosting and orchestration.

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Security & Best Practices

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Implement secure API design based on OWASP API Security guidelines.

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Follow secure coding practices and data privacy guidelines.

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Ensure observability, logging, and error handling in production systems.

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Architecture & Design

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Translate functional requirements into technical designs and implementation plans.

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Design RAG pipelines and Agentic AI flows using LangGraph DAG-based orchestration.

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Create architecture diagrams and solution documentation using draw.io.

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Required Technical Skills

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AI & GenAI

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LangChain

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LangGraph

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RAG pipeline implementation

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LLM inferencing pipelines

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Agentic AI workflows

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Programming

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Python

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NestJS (Node.js framework)

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Databases

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Vector Databases (either of below)

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otpgVector otOpenSearch otMilvus

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Metadata Stores

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otPostgreSQL otAWS RDS

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APIs & Integration

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REST APIs

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Webhooks

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Secure API design

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OWASP API security standards

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Data Processing

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DAG-based workflows

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Apache Spark (basic working knowledge)

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Cloud Platforms

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AWS or GCP

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Tools draw.io

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Git-based development workflows

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Desired Skills

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Knowledge of LLM evaluation techniques

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Experience with embedding models and semantic search

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Experience with LLM observability and prompt engineering

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Understanding of agent orchestration patterns and multi-agent systems

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Exposure to MLOps / LLMOps practices

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Conceptual (Nice to have working) knowledge of DevOps

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Professional & Technical Skills:

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Candidate must have hands-on implementation experience in at least one of the following:

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RAG-based knowledge assistant

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LLM inferencing application

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Agentic AI workflow using LangChain / LangGraph

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Document ingestion and vector search pipeline

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Experience can come from industry projects, internships, research, or academic projects.

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Soft Skills

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Strong analytical and problem-solving skills

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Ability to quickly learn recent technologies and frameworks

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Experimen

Apply on Kit Job: kitjob.in/job/46vtad

📌 Application Support Engineer (Mumbai)
🏢 Accenture
📍 Mumbai