Agentic AI Engineer Recruitment 2026 | 0–2 Years | Python, GenAI, RAG, AWS

Details	Information
Job Role	Agentic AI Engineer
Experience	0–2 Years (Internships & Co-ops Accepted)
Job Type	Full-Time
Qualification	Bachelor's/Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or Related Field
Skills	Python, Java, GenAI, LLMs, RAG, AWS, Azure, GCP

Introduction

An exciting opportunity is available for an Agentic AI Engineer to work on cutting-edge AI-powered enterprise solutions focused on supply chain automation. This role is ideal for fresh graduates and early-career professionals passionate about Generative AI, Agentic AI systems, Retrieval-Augmented Generation (RAG), and backend software development.

You will collaborate with experienced engineers and data scientists to develop intelligent AI applications, improve knowledge retrieval systems, build production-grade backend services, and contribute to the next generation of enterprise AI solutions.

About the Role

As an Agentic AI Engineer, you will design, build, and enhance AI-powered applications that automate real-world business workflows. The role combines software engineering, machine learning, and Generative AI technologies to solve complex enterprise problems.

Eligibility Criteria

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related discipline.
0–2 years of professional experience.
Internships and co-op experience are considered.
Strong programming skills in Python and/or Java.
Passion for Artificial Intelligence and Generative AI.

Required Skills

Python
Java
Generative AI
Large Language Models (LLMs)
Agentic AI
Retrieval-Augmented Generation (RAG)
REST APIs
AWS / Azure / GCP
Data Structures & Algorithms
Distributed Systems Basics

Roles & Responsibilities

Design and develop Agentic AI and Generative AI solutions for enterprise supply chain workflows.
Build and maintain backend services using Python and/or Java.
Develop multi-agent workflows, tool execution pipelines, and task orchestration systems.
Create and improve AI testing, validation, and evaluation strategies.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines.
Improve knowledge retrieval using embeddings, hybrid search, reranking, and grounding techniques.
Experiment with lightweight fine-tuning methods for Small Language Models (SLMs).
Support reinforcement learning-inspired improvements for NLP and Generative AI tasks.
Collaborate with product, engineering, and domain experts to deliver AI solutions.
Participate in code reviews, documentation, debugging, and production support.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
0–2 years of experience in AI Engineering, ML Engineering, or Software Engineering.
Internship or co-op experience is considered.
Strong programming skills in Python and/or Java.
Knowledge of REST APIs and backend development.
Understanding of distributed systems fundamentals.
Experience with AWS, Azure, or Google Cloud Platform.
Strong debugging and problem-solving abilities.
Excellent communication and teamwork skills.

Preferred Qualifications

Experience with Agentic AI or Multi-Agent Systems.
Knowledge of Retrieval-Augmented Generation (RAG).
Experience with embeddings, vector databases, hybrid search, and reranking.
Exposure to LLM fine-tuning or Small Language Models (SLMs).
Knowledge of Reinforcement Learning concepts.
Experience with NLP projects.
Understanding of event-driven architectures.
Interest in Supply Chain, Manufacturing, Logistics, or Procurement.
Knowledge of Life Sciences Supply Chain is an added advantage.

Technical Skills

Python
Java
Generative AI
Large Language Models (LLMs)
Agentic AI
RAG
Vector Databases
Embeddings
Hybrid Search
Prompt Engineering
REST APIs
AWS
Microsoft Azure
Google Cloud Platform (GCP)
Distributed Systems
Data Structures & Algorithms
Software Engineering
Machine Learning
Natural Language Processing (NLP)

What Success Looks Like

Deliver AI features with guidance from senior engineers.
Develop reliable and maintainable production-quality code.
Improve AI evaluation and system reliability.
Build scalable knowledge retrieval solutions.
Contribute to enterprise AI products solving real-world business problems.

Who Should Apply?

Fresh graduates interested in AI Engineering.
Candidates with up to 2 years of experience.
Applicants passionate about Generative AI and Machine Learning.
Software Engineers looking to transition into AI Engineering.
Candidates interested in enterprise AI applications.

Interview Preparation Tips

Revise Python and Java programming concepts.
Study Large Language Models and Prompt Engineering.
Understand RAG architecture and Vector Databases.
Practice API development and backend fundamentals.
Review cloud platform basics (AWS, Azure, GCP).
Strengthen Data Structures and Algorithms concepts.
Prepare AI and Machine Learning project discussions.

How to Apply

Interested candidates should apply through the company's official careers page using the below link

Apply Now

Resume Tips for This Role

Keep your resume ATS-friendly and limited to one or two pages.
Highlight projects involving Generative AI, Machine Learning, or backend development.
Showcase hands-on experience with Python, Java, APIs, or cloud platforms.
Include internships, research work, hackathons, or AI certifications.
Mention projects using LLMs, RAG, vector databases, or prompt engineering.
Demonstrate problem-solving, debugging, and collaboration skills.

Frequently Asked Questions (FAQs)

1. Who can apply?

Candidates with a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related fields with 0–2 years of experience can apply.

2. Are freshers eligible?

Yes. Fresh graduates, interns, and candidates with internship or co-op experience are encouraged to apply.

3. Which programming languages are required?

Strong knowledge of Python and/or Java is required.

4. Which AI technologies should I know?

Knowledge of LLMs, Agentic AI, RAG, Prompt Engineering, Vector Databases, and cloud platforms is highly preferred.

5. Is cloud experience mandatory?

Academic, personal, or internship experience with AWS, Azure, or GCP is acceptable.

Key Takeaways

Agentic AI Engineer Role.
0–2 Years Experience.
Freshers Eligible.
Python & Java Development.
Generative AI & LLMs.
Retrieval-Augmented Generation (RAG).
Cloud Platforms (AWS, Azure, GCP).
Enterprise AI & Supply Chain Solutions.

Top Skills Recruiters Look For

Python
Java
Generative AI
Large Language Models (LLMs)
Agentic AI
RAG
Vector Databases
Prompt Engineering
AWS / Azure / GCP
REST APIs
Machine Learning
Problem Solving

Common Interview Questions

Explain Retrieval-Augmented Generation (RAG).
What are Agentic AI systems?
Describe a Generative AI project you have worked on.
How do vector databases work?
Explain prompt engineering and tool calling.
How would you evaluate an LLM application?
What challenges arise with non-deterministic AI systems?

How to Stand Out for This Role

Build projects using LLMs and RAG pipelines.
Practice Python backend development.
Create AI applications using OpenAI or open-source LLMs.
Learn cloud deployment fundamentals.
Contribute to open-source AI projects.
Build a GitHub portfolio showcasing AI projects.

ATS Resume Keywords

Agentic AI
Generative AI
LLM
RAG
Python
Java
Vector Database
Prompt Engineering
Machine Learning
Artificial Intelligence
AWS
Azure
GCP
REST API
Backend Development

Conclusion

The Agentic AI Engineer opportunity is ideal for fresh graduates and early-career professionals looking to build enterprise-scale AI applications using Generative AI, LLMs, RAG, and cloud technologies. It offers an excellent platform to develop practical AI engineering skills while solving real-world business challenges.

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Disclaimer

The information provided in this article is based on the official job description available at the time of writing. Recruitment details and eligibility criteria may change without prior notice. Candidates are advised to verify the latest information through the official recruitment source before applying.

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