Qualcomm AI Platform Engineer Recruitment 2026 | Freshers Apply

Qualcomm AI Platform Engineer Recruitment 2026 | Freshers Apply

Qualcomm India is hiring candidates for the Engineer/Associate Engineer – AI Platform role. This opportunity is part of Qualcomm’s Enterprise AI team, which focuses on accelerating Artificial Intelligence adoption across the organization by building enterprise AI platforms, AI agents, Large Language Model applications, RAG systems, developer tools, and intelligent automation solutions.

The opportunity is suitable for candidates with a Bachelor’s or Master’s degree in Computer Science or a related field. Candidates with 0–1 year of experience can apply, and the job description specifically encourages exceptional fresh graduates. Applicants with strong Computer Science fundamentals, programming skills, backend development knowledge, problem-solving ability, and an interest in AI technologies are well aligned with this role.

Quick Job Snapshot

Company Name	Qualcomm India Private Limited
Role	Engineer/Associate Engineer – AI Platform
Job ID	3093492
Job Area	Engineering Group – Software Engineering
Qualification	Bachelor’s or Master’s Degree in Computer Science or Related Field
Experience	0–1 Year / Exceptional Fresh Graduates
Salary	₹12–22 LPA (Estimated)
Job Type	Full-Time

About the Enterprise AI Team

Qualcomm’s Enterprise AI team focuses on building end-to-end Artificial Intelligence solutions that improve engineering productivity through intelligent automation and modern AI technologies. The team works across enterprise AI platforms, developer tools, AI agents, agentic workflows, LLM applications, model deployment, inference systems, RAG pipelines, knowledge systems, and AI infrastructure.

Engineers in this team have opportunities to collaborate closely with domain engineering teams and solve real-world technical problems using modern Artificial Intelligence technologies. The role can provide exposure to large-scale AI systems that support software engineering and enterprise technology workflows.

Key Areas of Work

• Enterprise AI platforms and developer productivity tools.
• Artificial Intelligence agents and agentic workflows.
• Large Language Model applications.
• LLM post-training pipelines.
• Enterprise-scale model deployment and inference.
• Retrieval-Augmented Generation systems.
• Knowledge systems and vector databases.
• AI infrastructure and model orchestration.
• Backend systems and scalable APIs.
• Intelligent automation for engineering teams.
• Collaboration with domain engineering teams to solve real-world problems.

Candidate Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Strong academic background.
• CGPA/GPA of 8.5 or above is preferred.
• 0–1 year of professional experience.
• Exceptional fresh graduates are encouraged to apply.
• Strong foundation in Data Structures and Algorithms.
• Good understanding of Operating Systems.
• Knowledge of Computer Networks.
• Strong understanding of DBMS concepts.
• Knowledge of Object-Oriented Programming.
• Ability to write clean, efficient, and scalable code.
• Strong analytical and problem-solving ability.
• Understanding of backend systems and software engineering principles.
• Passion for learning AI technologies and building impactful software solutions.

Preferred Programming Skills

Candidates with programming experience in Python, Java, C++, or similar programming languages will have an advantage. Java is mentioned as a preferred language, while Python is particularly useful for Artificial Intelligence, Machine Learning, backend APIs, data processing, and Generative AI applications.

Candidates should be comfortable with coding, debugging, writing scalable software, understanding existing codebases, and applying software engineering best practices. Strong Data Structures and Algorithms knowledge can also be important for coding assessments and technical interviews.

Backend Development Skills

• REST API development.
• FastAPI or Flask.
• Microservices architecture.
• Distributed systems fundamentals.
• Backend application development.
• Software design principles.
• Scalable application architecture.
• Testing and debugging.

Database and Data Engineering Skills

Candidates with knowledge of SQL databases, NoSQL databases, data modeling, and vector databases will have an advantage. The role also values exposure to Data Engineering concepts such as ETL pipelines, data processing, and data management fundamentals.

Since modern AI applications depend heavily on data pipelines and retrieval systems, candidates should understand how structured and unstructured data can be processed, stored, retrieved, and integrated into AI-powered applications.

Artificial Intelligence and Machine Learning Skills

• Machine Learning fundamentals.
• Basic understanding of Deep Learning.
• Practical exposure to Generative AI.
• Large Language Model fundamentals.
• Prompt Engineering.
• Context Engineering.
• Retrieval-Augmented Generation (RAG).
• AI Agents and Agentic Workflows.
• Embeddings and Vector Search.
• Model orchestration frameworks.
• Model deployment and inference concepts.

Cloud and DevOps Skills

Exposure to Docker, Kubernetes, Git, CI/CD pipelines, and cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform is preferred. Candidates should understand basic software deployment workflows, containerization, version control, automated delivery pipelines, and cloud-based application environments.

Skills Candidates Should Prepare

Candidates preparing for this opportunity should first strengthen Computer Science fundamentals, particularly Data Structures and Algorithms, Object-Oriented Programming, DBMS, Operating Systems, and Computer Networks. Strong coding ability in Python, Java, or C++ should be combined with practical backend development skills such as REST APIs, FastAPI, Flask, SQL, and Git.

For the AI component, candidates should understand Machine Learning basics, Generative AI, LLMs, prompt engineering, embeddings, vector databases, RAG pipelines, and AI agents. Building practical projects such as a document Q&A application, RAG chatbot, AI coding assistant, multi-agent workflow, semantic search engine, or LLM-powered API can help candidates demonstrate relevant technical experience.

Salary Insights

Qualcomm has not officially disclosed the salary package for this position in the provided job description. Based on comparable entry-level software engineering and AI engineering opportunities at leading semiconductor and technology companies in India, the estimated annual compensation may range between ₹12 LPA and ₹22 LPA. Actual compensation may vary depending on role level, candidate profile, technical skills, educational background, interview performance, benefits, and company compensation policies.

Career Growth Opportunities

The Engineer/Associate Engineer – AI Platform role can provide a strong foundation for careers in Artificial Intelligence Engineering, Generative AI, Machine Learning Engineering, Backend Development, AI Platform Engineering, Data Engineering, MLOps, and Software Engineering.

With relevant experience and continued technical development, professionals may progress toward roles such as AI Engineer, Machine Learning Engineer, Generative AI Engineer, LLM Engineer, AI Platform Engineer, Backend Engineer, Data Engineer, MLOps Engineer, Senior Software Engineer, AI Solutions Architect, or Technical Lead.

🎯 Interview Preparation

For the Qualcomm Engineer/Associate Engineer – AI Platform role, candidates should prepare Data Structures & Algorithms (DSA), Object-Oriented Programming (OOP), Operating Systems, Computer Networks, DBMS, SQL, backend development, system design fundamentals, debugging, and software testing concepts. Candidates should be comfortable writing clean and efficient code in at least one programming language such as Python, Java, or C++.

For the Artificial Intelligence portion of the interview, candidates should prepare Machine Learning fundamentals, Deep Learning basics, Generative AI, Large Language Models (LLMs), prompt engineering, context engineering, embeddings, vector databases, Retrieval-Augmented Generation (RAG), AI agents, agentic workflows, and model orchestration concepts. Candidates should understand how an LLM-powered application works from user query processing to retrieval, prompt construction, model inference, and response generation.

Candidates should also prepare backend development concepts such as REST APIs, HTTP methods, API authentication, FastAPI or Flask, microservices, databases, caching, distributed systems basics, and application scalability. For Cloud and DevOps preparation, revise Docker, Kubernetes fundamentals, Git, CI/CD pipelines, and basic concepts of AWS, Azure, or GCP.

During technical interviews, candidates should be prepared to explain academic projects, internships, AI applications, backend projects, GitHub repositories, hackathon participation, and open-source contributions. For each project, clearly explain the problem statement, architecture, technology stack, your individual contribution, challenges faced, performance considerations, testing approach, and final outcome.

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How to Apply for Qualcomm AI Platform Engineer Recruitment 2026

Interested candidates can apply through the official Qualcomm Careers portal. Before submitting the application, candidates should update their resume to highlight programming skills, Computer Science fundamentals, backend development experience, AI/ML projects, Generative AI applications, internships, technical certifications, hackathons, open-source contributions, and GitHub projects.

1. Click the Apply Now button provided below.
2. Visit the official Qualcomm Careers application page.
3. Read the complete job description and candidate requirements carefully.
4. Create a candidate account or sign in to your existing profile.
5. Enter accurate personal, educational, and professional information.
6. Add relevant programming languages, backend technologies, databases, AI/ML skills, and cloud technologies.
7. Include AI projects, internships, academic projects, certifications, hackathons, and relevant technical achievements.
8. Upload your latest resume and any other required documents.
9. Review the complete application carefully before submission.
10. Submit the application and regularly monitor your registered email and candidate portal for recruitment updates.

🚀 Apply Now – Qualcomm

Frequently Asked Questions (FAQs)

1. What is the role offered by Qualcomm?

Qualcomm is hiring for the Engineer/Associate Engineer – AI Platform role within its Engineering Group. The position is associated with the Enterprise AI team, which works on enterprise AI platforms, AI agents, agentic workflows, LLM applications, model deployment, RAG systems, knowledge systems, developer tools, and AI infrastructure.

2. Who can apply for the Qualcomm AI Platform role?

The job description mentions candidates with a Bachelor’s or Master’s degree in Computer Science or a related field. The general minimum qualification also mentions a Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field. Candidates should review the official application page carefully before applying.

3. Can fresh graduates apply?

Yes. The candidate requirements mention 0–1 year of experience and state that exceptional fresh graduates are encouraged to apply. Candidates should demonstrate strong Computer Science fundamentals, coding ability, problem-solving skills, software engineering knowledge, and genuine interest in AI technologies.

4. Is an 8.5 CGPA mandatory for this role?

The job description states that a strong academic record is expected and mentions a CGPA/GPA of 8.5 or above as preferred. Based on the wording provided, this is listed as a preference rather than an absolute minimum qualification.

5. Which programming languages are preferred?

The preferred technical skills include Python, Java, C++, or similar programming languages, with Java specifically mentioned as preferred. Candidates should develop strong coding and problem-solving ability in at least one language while also understanding clean code, debugging, testing, and scalable software development principles.

6. What AI skills should candidates prepare?

Candidates should prepare Machine Learning fundamentals, Deep Learning basics, Generative AI, LLMs, prompt engineering, context engineering, embeddings, vector databases, RAG, AI agents, agentic workflows, and model orchestration frameworks. Practical implementation experience through AI projects can significantly strengthen interview preparation.

7. What backend development skills are useful for this role?

Useful backend skills include REST APIs, FastAPI, Flask, microservices, distributed systems fundamentals, software design principles, SQL, NoSQL, data modeling, and vector databases. Candidates should understand how backend services interact with databases, AI models, external APIs, and client applications.

8. Are Cloud and DevOps skills required?

Cloud and DevOps technologies are listed as preferred skills. Exposure to Docker, Kubernetes, Git, CI/CD, AWS, Azure, or GCP can provide an advantage. Candidates should understand containerization, version control, automated deployment workflows, and basic cloud architecture concepts.

9. What is the expected salary for the Qualcomm AI Platform Engineer role?

Qualcomm has not officially disclosed the salary package in the provided job description. Based on comparable entry-level AI and software engineering opportunities at leading semiconductor and technology companies in India, an estimated annual compensation range may be around ₹12 LPA to ₹22 LPA. Actual compensation may vary depending on role level, candidate profile, skills, educational background, benefits, and company compensation policies.

10. What projects can help candidates prepare for this role?

Relevant projects may include a RAG-based document question-answering application, enterprise knowledge assistant, semantic search engine, AI coding assistant, multi-agent workflow, LLM-powered API, intelligent document processing system, recommendation engine, or AI-powered developer productivity tool. Candidates should focus on understanding the complete architecture rather than only connecting an application to an external AI API.

Why Consider This AI Platform Opportunity?

The Qualcomm Engineer/Associate Engineer – AI Platform role combines core Software Engineering with modern Artificial Intelligence technologies. Candidates can gain exposure to backend development, enterprise AI platforms, Generative AI, LLM applications, AI agents, RAG systems, data infrastructure, model deployment, and large-scale engineering workflows.

This opportunity can be particularly relevant for candidates who have strong Computer Science fundamentals and want to build careers at the intersection of Software Engineering and Artificial Intelligence. Candidates should focus on strengthening DSA, programming, backend development, databases, AI fundamentals, LLM application development, cloud technologies, and practical project experience while preparing for the recruitment process.