Senior Application Developer

Quess IT Solutions

Bengaluru

On-site

INR 4,000,000 - 7,000,000

Full time

6 days ago
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Job summary

Quess IT Solutions is seeking an experienced engineer to lead the development of Agentic AI platforms and full‑stack applications. You will design multi‑agent RAG systems, architect cloud-native solutions, and mentor teams.

You will work with Python backends, FastAPI, Django, Vue.js frontends, and Kubernetes, delivering scalable AI-powered enterprise apps with strong governance and security.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, AI, or related field.
  • 5+ years of software engineering experience.
  • 3+ years building AI-powered applications, LLM solutions, Agentic AI systems, or automation platforms.
  • Hands-on experience with LangChain and LangGraph for enterprise AI agents.

Responsibilities

  • Design and develop Agentic AI solutions using LLMs, AI Agents, multi-agent systems, and RAG architectures.
  • Build AI-powered business apps integrating conversational AI, automation, and decision intelligence.
  • Lead and mentor engineering teams; drive Agile delivery and engineering excellence.
  • Develop Python backends, FastAPI, Django, REST APIs, and Vue.js frontends; enable scalable microservices.

Skills

Python
FastAPI
Vue.js
Cloud-native
LLMs
RAG
AI Agents
Agentic Workflows
Team leadership
Agile

Education

Bachelor's or Master's in CS or related

Tools

LangChain
LangGraph
Kubernetes
AWS/Azure
Django

Job description

Job Role

This role combines software engineering, AI engineering, cloud-native architecture, and technical leadership to deliver scalable enterprise solutions across retail and group functions.

The ideal candidate will possess strong expertise in Python backend development, Vue.js frontend engineering, cloud-native architecture, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Agentic Workflows. The role requires hands-on technical leadership while mentoring engineers and driving engineering excellence across the team.

You will be responsible for building intelligent business applications that seamlessly combine traditional software capabilities with AI-driven automation, decision support, and autonomous agent execution.

Agentic AI Solution Development
  • Design and develop enterprise-grade Agentic AI solutions leveraging LLMs, AI Agents, Multi-Agent Systems, and Retrieval-Augmented Generation (RAG) architectures.
  • Build intelligent agents capable of reasoning, planning, tool usage, workflow orchestration, and autonomous task execution.
  • Develop AI-powered business applications integrating conversational AI, automation, enterprise knowledge retrieval, and decision intelligence.
Design and implement multi-agent systems that collaborate to solve complex business challenges across retail and corporate functions.

Establish best practices for prompt engineering, context management, agent memory, evaluation, monitoring, and governance.

Evaluate emerging AI technologies, models, frameworks, and tools to continuously enhance platform capabilities.

Full Stack Application Development

Build mission-critical enterprise applications using Python-based backend frameworks and Vue.js frontend technologies.

Design and develop scalable APIs and microservices supporting AI-powered and Full Stack Application Development traditional business workflows.

Create intuitive and responsive user experiences that seamlessly integrate AI capabilities into business processes.

Develop real-time applications supporting conversational interfaces, workflow automation, and intelligent decision support.

Follow software engineering best practices to deliver scalable, maintainable, and secure solutions.

Architecture & Engineering

Design cloud-native architectures that are scalable, resilient, secure, and maintainable.

Define architectural patterns for Agentic AI systems, enterprise AI platforms, and business applications.

Drive adoption of microservices, event-driven architectures, API-first design, and domain-driven design principles.

Lead technical design reviews and architecture discussions.

Establish coding standards, reusable frameworks, engineering accelerators, and development best practices.

Cloud & Platform Engineering

Develop and deploy applications on Kubernetes-based infrastructure (AKS preferred).

Design and maintain CI/CD pipelines supporting rapid and reliable software delivery.

Implement observability through monitoring, logging, tracing, alerting, and AI evaluation frameworks.

Ensure applications meet enterprise standards for security, performance, scalability, and reliability.

Collaborate with platform teams to optimize cloud infrastructure and deployment strategies.

Leadership & Delivery

Lead and mentor engineering teams to deliver AI-powered products and business applications.

Collaborate with Product Managers, Architects, Data Scientists, and Business Stakeholders throughout the solution lifecycle.

Drive Agile delivery practices and engineering excellence across the team.

Participate in estimation, roadmap planning, technical strategy, and release governance.

Foster a culture of innovation, experimentation, ownership, and continuous learning.

Who are we looking for?
Education
  • Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or related discipline.
Experience
  • 5+ years of software engineering experience.
  • 5+ years of experience developing server backends such as Web APIs using object-oriented programming or functional programming.
  • 5+ years of experience developing cloud applications using AWS/ Azure/on prem Linux/equivalent technologies or platform.
  • 3+ years of experience building AI-powered applications, LLM solutions, Agentic AI systems, or intelligent automation platforms.
  • Hands-on experience with LangChain and LangGraph for building and deploying enterprise-grade AI agents and agentic workflows.
  • Proven experience leading engineering teams and delivering enterprise-scale software solutions.
  • Experience working within Agile product development environments.
Technical Skills
AI & Agentic Technologies
  • Large Language Models (LLMs)
  • Agentic AI Systems
  • Multi-Agent Architectures
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Agent Memory & Context Management
  • AI Evaluation Frameworks
  • Responsible AI & AI Governance
Preferred Frameworks
  • LangGraph
  • Semantic Kernel
  • Model Context Protocol (MCP)
  • LangChain
  • Azure AI Foundry
  • Generative AI Platforms
  • Azure OpenAI
  • OpenAI Models
  • Anthropic Claude
  • Google Gemini
  • Open-source LLMs (Llama, Mistral, DeepSeek)
Generative AI Platforms
  • Azure AI Search
  • Vector Databases
  • Elasticsearch
Backend Development
  • Python
  • FastAPI
  • Flask
  • Django
  • REST APIs
  • Event-Driven Architecture
  • Microservices
  • Async Programming
Knowledge Systems & Search
  • Azure AI Search
  • Vector Databases
  • Elasticsearch
Backend Development
  • Python
  • FastAPI
  • Flask
  • Django
  • REST APIs
  • Event-Driven Architecture
  • Microservices
  • Async Programming
Cloud & Infrastructure
  • Microsoft Azure
  • Kubernetes (AKS)
  • Docker
  • Azure Container Registry
  • Azure Key Vault
  • Azure Functions
  • Azure Service Bus
  • Azure Event Hub
Databases & Data Platforms
  • PostgreSQL
  • SQL Server
  • Redis
  • MongoDB
DevOps & Platform Engineering
  • Git
  • Azure DevOps
  • CI/CD Pipelines
Observability & Monitoring
  • Azure Application Insights
  • Monitoring & Alerting Frameworks
  • AI Performance Monitoring
  • Cost & Usage Monitoring
Backend Development
  • Python
  • FastAPI
  • Flask
  • Django
  • REST APIs
  • Event-Driven Architecture
  • Microservices
  • Async Programming
Backend Development
  • Python
  • FastAPI
  • Flask
  • Django
  • REST APIs
  • Event-Driven Architecture
  • Microservices
  • Async Programming
Critical Competencies
  • Builds and scales high-performing engineering teams.
  • Demonstrates strong ownership and accountability.
  • Create, update, and maintain LLDs FSDs and technical documentation.
  • Balances innovation with operational excellence.
  • Strong problem-solving and system-thinking mindset.
  • Ability to translate business challenges into scalable AI-powered solutions.
  • Customer-focused with a passion for delivering measurable business impact.
  • Influences stakeholders through technical expertise and collaboration.
  • Passionate about emerging AI technologies and continuous learning.
  • Drives engineering excellence through mentoring, standards, and best practices.
  • Thrives in fast-paced environments with a strong bias for action.
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