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🚀 GIVA AI Engineer 1 Hiring 2026 | Bengaluru | Freshers (0–2 Years) | Build GenAI & Agentic AI Applications | Placement Officer
📌 Detailed Summary
Are you passionate about Artificial
Intelligence, Generative AI, Large Language Models (LLMs), Python, LangChain,
Agentic AI, and Software Engineering? GIVA, one of India's
fastest-growing jewellery brands with over 350+ stores, is hiring AI
Engineer 1 in Bengaluru.
This is an exciting opportunity for
recent graduates and professionals with 0–2 years of experience who have
a strong engineering background and hands-on AI projects. Unlike traditional AI
roles focused on research, this position is all about building
production-ready AI applications, integrating LLMs, implementing Retrieval-Augmented
Generation (RAG), developing AI Agents, and deploying intelligent
automation solutions.
If you've built AI projects using Python,
OpenAI, Claude, LangChain, Hugging Face, vector databases, or MCP, this
role could be your gateway into one of the most in-demand AI careers in 2026.
🌟 GIVA Hiring AI Engineer 1 | Bengaluru | Freshers Can Apply | GenAI & Agentic AI Jobs 2026
📍 Job Overview
|
Particular |
Details |
|
Company |
GIVA |
|
Role |
AI Engineer
1 |
|
Job Type |
Full-Time |
|
Experience |
0–2 Years |
|
Location |
Bengaluru,
Karnataka |
|
Work Mode |
On-Site |
|
Department |
Technology /
Product & Engineering |
|
Reports To |
Head of Data
& AI Initiatives |
🏢 About GIVA
GIVA is one of India's leading
jewellery brands with 350+ physical stores across India and
international markets. Beyond retail, GIVA has built a strong in-house
technology ecosystem that powers its warehouses, ERP systems, logistics,
customer experience, and business operations.
The company's AI Engineering team
is focused on creating next-generation AI products using Large
Language Models (LLMs), AI Agents, RAG, and intelligent automation, making
it an exciting workplace for engineers looking to work on real-world AI
applications.
🎓 Eligibility Criteria
Educational Qualification
The job description emphasizes a
strong engineering and machine learning background.
Preferred qualifications include:
·
✅ B.E.
·
✅ B.Tech.
·
✅ M.Tech.
·
✅ MCA
·
✅ Computer
Science
·
✅ Artificial
Intelligence
·
✅ Machine Learning
·
✅ Data Science
·
✅ Information
Technology
·
✅ Related
Engineering Disciplines
Experience
·
Fresh
Graduates
·
0–2 Years
Experience
🎯 Eligible Batches
Based on the job description and
experience requirements:
·
✅ 2024 Graduates
·
✅ 2025
Graduates
·
✅ 2026
Graduates
Candidates with exceptional AI
projects, hackathons, or GitHub portfolios will have a competitive advantage.
💼 Detailed Job Description
As an AI Engineer 1, your
primary responsibility is to build production-ready AI applications that
leverage Large Language Models (LLMs) and Agentic AI systems.
Instead of performing traditional
machine learning research, you'll design, develop, test, deploy, and maintain
AI-powered software capable of solving real business problems.
You'll collaborate closely with
Product Managers and business stakeholders to build intelligent systems that
automate workflows, retrieve enterprise knowledge, interact with APIs, and
improve customer and business operations.
🛠 Key Responsibilities
🤖 Build AI Applications
·
Develop
applications powered by Large Language Models (LLMs)
·
Integrate AI
APIs into production software
·
Design prompt
engineering workflows
·
Implement
Model Context Protocols (MCP)
📚 Build RAG Systems
·
Implement
Retrieval-Augmented Generation (RAG)
·
Create
embeddings
·
Chunk
enterprise documents
·
Configure
vector search pipelines
🧠 Develop AI Agents
·
Build
autonomous AI agents
·
Automate
multi-step workflows
·
Integrate
external tools
·
Handle failure
recovery
📊 AI Evaluation & Optimization
·
Build
evaluation datasets
·
Perform A/B
testing
·
Tune prompts
·
Improve AI
accuracy
🚀 Production Engineering
·
Deploy AI
applications
·
Monitor
performance
·
Track
operational costs
·
Maintain
logging systems
🔍 Model Selection
·
Evaluate
OpenAI models
·
Compare
Anthropic Claude
·
Analyze Google
Gemini
·
Explore
open-source LLMs
·
Select the
best model based on cost, latency, and accuracy
💻 Essential Skills Required
Programming
·
Python
·
Git
·
Debugging
·
Software
Engineering Fundamentals
Artificial Intelligence
·
Large Language
Models (LLMs)
·
Prompt
Engineering
·
AI Agents
·
Retrieval-Augmented
Generation (RAG)
·
Embeddings
·
Vector Search
·
MCP (Model
Context Protocol)
AI Development
·
API
Integration
·
Production
Deployment
·
Logging
·
Monitoring
·
AI Evaluation
Software Engineering
·
System Design
·
Problem
Solving
·
Version
Control
·
Documentation
Soft Skills
·
Communication
·
Product
Thinking
·
Ownership
·
Adaptability
·
Continuous
Learning
⭐ Good-to-Have Skills
🦜 LangChain
🕸 LangGraph
🤗 Hugging Face
📂 Pinecone
🔎 Weaviate
🧠 ChromaDB
☁️ Cloud Deployment
📊 Monitoring
⚙️ Cost Optimization
🌍 Public GitHub Portfolio
📝 Technical Blogs
🌟 Why You Should Apply
🤖 Work on Production AI
Applications
🧠 Build Agentic AI Systems
📚 Implement Enterprise RAG
Pipelines
🚀 Learn End-to-End AI
Engineering
💼 Collaborate with Product
Teams
🌟 Exposure to Multiple
Foundation Models
📈 Rapid Career Growth
🏢 Join a Fast-Growing
Technology-Driven Brand
💰 Expected Salary (Market Comparison)
GIVA has not officially
disclosed the compensation for this position.
Based on comparable AI Engineer,
Generative AI Engineer, and LLM Engineer roles in Bengaluru:
|
Experience |
Expected Annual CTC |
|
Freshers |
₹8 – ₹12 LPA |
|
1–2 Years |
₹10 – ₹16 LPA |
Additional Benefits
·
Performance-Based
Appraisals
·
Learning
Opportunities
·
AI Project
Exposure
·
Career Growth
·
Cross-Functional
Collaboration
The actual salary may vary
depending on interview performance, skills, experience, and company
compensation policies.
🚀 Career Growth Opportunities
Joining GIVA as an AI Engineer can
lead to exciting roles such as:
·
Generative AI
Engineer
·
LLM Engineer
·
AI Platform
Engineer
·
Machine
Learning Engineer
·
Applied AI
Engineer
·
AI Solutions
Engineer
·
Senior AI
Engineer
·
AI Architect
·
Technical Lead
– AI
🌟 Unique Highlights
🤖 Build Real Production AI
Systems
🧠 Work with Agentic AI
📚 Build Enterprise RAG
Solutions
⚡ Compare OpenAI, Anthropic &
Gemini Models
🚀 Own Complete AI Product
Lifecycle
🌍 Work Directly with
Business Teams
💻 Focus on Engineering, Not
Just Research
📈 Strong Learning &
Growth Environment
🎯 Pro Tips to Crack the Interview
✅ Build and publish at least one
end-to-end AI application using Python and an LLM API (OpenAI, Claude, Gemini,
or similar).
✅ Learn LangChain, LangGraph,
and RAG fundamentals, including embeddings, chunking, and vector
databases like Pinecone or Chroma.
✅ Practice prompt engineering
techniques and explain how you evaluate model outputs using test datasets and
A/B testing.
✅ Showcase your GitHub repositories
with clean code, documentation, and deployment instructions.
✅ Strengthen Python fundamentals,
API integration, debugging, and software engineering best practices.
✅ Understand AI deployment concepts
such as logging, monitoring, latency, and cost optimization.
✅ Be prepared to explain the design
decisions behind your AI projects, including why you chose a particular model
or architecture.
❓ Frequently Asked Questions (FAQs)
1. Who can apply?
Recent graduates and professionals
with 0–2 years of experience who have a strong software engineering and
AI background.
2. Is prior industry experience mandatory?
No. Strong academic projects,
hackathons, or personal AI applications are highly valued.
3. What programming language is required?
Python is the primary programming
language expected for this role.
4. Is this a research role?
No. This is an engineering-focused
role involving the development and deployment of production AI applications.
5. Which AI technologies should candidates know?
Knowledge of LLMs, RAG, AI Agents,
Prompt Engineering, LangChain, Hugging Face, and vector databases is
advantageous.
6. Is cloud or deployment experience necessary?
Not mandatory, but experience with
deployment, monitoring, and production systems is a plus.
7. What is RAG?
Retrieval-Augmented Generation
(RAG) is an AI architecture that enhances language model responses by retrieving
relevant information from external knowledge sources.
8. Does GIVA require a GitHub portfolio?
A public GitHub profile or
documented AI projects is strongly preferred and can significantly strengthen
your application.
9. What work mode is offered?
This is a full-time, on-site
role based in Bengaluru.
10. What makes this role unique?
It emphasizes building
production-ready AI systems, AI agents, and enterprise-grade LLM
applications rather than only experimenting with machine learning models.
🏁 Conclusion
The GIVA AI Engineer 1
opportunity is ideal for aspiring AI engineers who want to work on real-world Generative
AI, LLMs, Agentic AI, and Retrieval-Augmented Generation (RAG) solutions.
With exposure to modern AI frameworks, production deployment, and end-to-end
software engineering, this role offers an outstanding platform to launch a
career in one of the fastest-growing areas of technology. Candidates with
strong Python skills, practical AI projects, and a passion for building
intelligent applications should not miss this opportunity.
🔗 Apply Link: Click Here To Apply for GIVA
|
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