Application Support Engineer
Mumbai
Job No. atci-5490980-s2002801
Full-time
工作描述
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 0-2 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:
o 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:
o Containerized workloads and working knowledge on dockers/ kubernetes
o AWS app services (incl. AWS Bedrock)
o 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)
o pgVector
o OpenSearch
o Milvus
Metadata Stores:
o PostgreSQL
o 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.
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 0-2 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:
o 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:
o Containerized workloads and working knowledge on dockers/ kubernetes
o AWS app services (incl. AWS Bedrock)
o 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)
o pgVector
o OpenSearch
o Milvus
Metadata Stores:
o PostgreSQL
o 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.
职位要求
15 years full time education
