Application Support Engineer

Project Role : Application Support Engineer

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

Must have skills : Python (Programming Language)

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

Minimum 2 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary

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.

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

Roles & Responsibilities

AI/GenAI Development

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

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

Develop agentic AI workflows and orchestration pipelines using LangGraph.

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

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

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

Backend & Microservices Development

Develop scalable microservices using NestJS and Python.

Design and build REST APIs with secure programming practices.

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

Develop DAG-based workflows and data pipelines.

Data & AI Infrastructure

Implement Vector Search And Semantic Retrieval Pipelines Using

• pgVector/ AWS OpenSearch/ Milvus
  
  

Design and manage metadata stores using PostgreSQL / AWS RDS.

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

Cloud & Platform Engineering

Build and deploy applications on AWS or GCP cloud platforms.

Implement Scalable AI Application Architectures Using

• Containerized workloads and working knowledge on dockers/ kubernetes
• AWS app services (incl. AWS Bedrock)
• Managed database services
  
  

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

Security & Best Practices

Implement secure API design based on OWASP API Security guidelines.

Follow secure coding practices and data privacy guidelines.

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

Architecture & Design

Translate functional requirements into technical designs and implementation plans.

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

Create architecture diagrams and solution documentation using draw.io.

Required Technical Skills

AI & GenAI

LangChain

LangGraph

RAG pipeline implementation

LLM inferencing pipelines

Agentic AI workflows

Programming

Python

NestJS (Node.js framework)

Databases

Vector Databases (either of below)

• pgVector
• OpenSearch
• Milvus
  
  

Metadata Stores

• PostgreSQL
• AWS RDS
  
  

APIs & Integration

REST APIs

Webhooks

Secure API design

OWASP API security standards

Data Processing

DAG-based workflows

Apache Spark (basic working knowledge)

Cloud Platforms

AWS or GCP

Tools

draw.io

Git-based development workflows

Desired Skills

Knowledge of LLM evaluation techniques

Experience with embedding models and semantic search

Experience with LLM observability and prompt engineering

Understanding of agent orchestration patterns and multi-agent systems

Exposure to MLOps / LLMOps practices

Conceptual (Nice to have working) knowledge of DevOps

Professional & Technical Skills

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

RAG-based knowledge assistant

LLM inferencing application

Agentic AI workflow using LangChain / LangGraph

Document ingestion and vector search pipeline

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

Soft Skills

Strong analytical and problem-solving skills

Ability to quickly learn new technologies and frameworks

Experimental mindset with innovation and prototyping capability

Strong communication and documentation skills

Ability to translate functional requirements into technical architecture

What We Value

We Are Looking For Engineers Who

Are curious about emerging AI technologies

Can rapidly prototype and demonstrate working solutions

Are comfortable experimenting in unknown problem spaces

Have the ability to translate AI concepts into production-grade systems

Additional Information

• The candidate should have minimum 2 years of experience in Java Full Stack Development.
• B.Tech / M.Tech/ Equivalent in Computer Science, AI, Data Science, or related fields.
• Candidates who have built GenAI projects during final year, internship, or industry experience will be preferred.
• This position is based at our Mumbai office.
• A 15 years full time education is required.