Senior Lead Engineer- Product Security tools, AI

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Software Engineering

General Summary:

As a leading technology innovator, Qualcomm pushes the boundaries of what’s possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.

Minimum Qualifications:

• Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
Master’s degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.

• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Location: Hyderabad

About the Role:

We are seeking an enthusiastic and versatile Senior Lead Engineer to join our dynamic team. The ideal candidate will have a strong software engineering background with the ability to seamlessly navigate multiple programming languages based on project and initiative needs. This role demands a proactive individual with expertise in automation, CI/CD pipelines, and advanced skills in AI/ML to drive end-to-end initiatives and deploy scalable applications.

 

Key Responsibilities

AI Agents & Intelligent Automation

• Build and operate Python-based automation frameworks for security and engineering workflows.
• Develop LLM-powered agentic systems, including single-agent and multi-agent reasoning patterns.
• Implement agent tool-calling and orchestration with internal systems (JIRA, static analysis tools, CI/CD, metadata services).
• Design context management pipelines (MCP-style patterns, memory, retrieval) for task-specific agent reasoning.
• Apply prompt engineering, guardrails, and evaluations to ensure reliable, auditable, and deterministic automation.

Python Automation & Backend Engineering

• Develop and maintain Python services, scripts, and APIs supporting AI-driven automation.
• Implement async, event-driven, or batch workflows based on scale and latency needs.
• Build lightweight integration APIs (FastAPI/Flask preferred).

Systems Integration & DevOps

• Package and deploy services using Docker and Kubernetes in enterprise environments.
• Integrate with CI/CD pipelines for continuous testing and safe rollout.
• Optimize systems for scalability, resiliency, and cost efficiency.
• Implement logging, tracing, and metrics for observability and debugging.

Collaboration & Engineering Excellence

• Partner with security, static analysis, and platform teams to automate manual workflows.
• Participate in design and architecture reviews; produce clear technical documentation.
• Mentor engineers on Python automation and AI agent best practices.

Required Qualifications

• 6–8+ years of experience with a Bachelor’s or master’s in computer science, Engineering, or related field.
• Proficiency in multiple programming languages (e.g., Python, Java, C++).
• Strong expertise in automation tools and CI/CD pipelines (e.g., Jenkins, Azure DevOps, GitHub Actions).
• Proven experience in AI/ML application development and deployment.
• Solid understanding of cloud platforms and container orchestration (Azure, AWS, Kubernetes).
• Excellent problem-solving, communication, and leadership skills.

 

Preferred Skills

• Experience with data engineering and big data technologies.
• Knowledge of security best practices in software development.
• Familiarity with DevOps culture and tools.
• Program Analysis
  • Automate build instantiation and generate artifacts like dependency graphs.
  • Work with static and dynamic analysis tools (e.g., CodeQL, Klocwork, fuzzing frameworks) to identify vulnerabil…