Senior Lead Engineer - Ai Platform Architecture & Engineering

Company: Qualcomm India Private Limited

Job Area: Engineering Group, Engineering Group > Software Engineering

Job Summary

We are seeking an experienced and highly motivated Senior Lead Engineer to lead the design, deployment, operationalization, and scaling of Generative AI (GenAI) solutions including orchestrator framework and deployment across enterprise and product environments.

The successful candidate will combine deep software engineering expertise with hands-on experience in building Agents, orchestrators, LLM-based applications, MLOps, cloud-native architectures, and production deployment of AI services. This individual will drive technical strategy, mentor engineering teams, architect scalable AI platforms, and ensure successful delivery of AI-powered solutions from concept through production.

This role requires strong leadership capabilities, exceptional technical depth, and a proven track record of deploying AI systems that deliver measurable business value.

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.

Job Summary

Preferably looking for master’s or Ph.D. with focus on deployment and application AI.

Key Responsibilities

• Lead design and implementation of scalable AI/ML platforms, building agents, orchestrator frameworks and enterprise AI infrastructure.
• Architect and deploy production-grade Generative AI, Machine Learning, and Agentic AI solutions.
• Build secure and reliable AI deployment pipelines and operational frameworks.
• Design AI services capable of supporting enterprise-scale workloads and high availability.

• Drive adoption of cloud-native AI technologies and modern deployment architectures.

• Develop end-to-end AI systems utilizing: LLMs, Retrieval-Augmented Generation (RAG), AI Agents and Multi-Agent Systems, Machine Learning and Deep Learning frameworks, NLP and Conversational AI, Computer Vision, Recommendation Systems, Predictive Analytics.
• Evaluate and select appropriate models, architectures, and deployment strategies.

MLOps AI Operations

• Establish and maintain MLOps best practices.
• CI/CD pipelines for AI workloads
• Model versioning
• Experiment tracking
• Automated retraining
• Model monitoring
• Drift detection
• Performance benchmarking
• Governance and auditability
• Ensure reliable deployment, operational monitoring, and lifecycle management of AI solutions.

Engineering Leadership

• Provide technical leadership across AI initiatives.
• Lead architecture reviews and technical design discussions.
• Mentor engineers and data scientists.
• Establish engineering standards, best practices, and reusable frameworks.
• Collaborate with senior leadership on AI strategy and roadmaps.

Product Cross-Functional Collaboration

• Partner with Product Management, Architecture, Security, IT, Data Engineering, and Business stakeholders.
• Translate business requirements into scalable technical solutions.
• Drive adoption of AI technologies throughout the software development lifecycle.

AI Governance, Security Compliance

• Ensure responsible AI practices and model governance.
• Implement security controls for AI systems and deployed models.
• Develop standards for privacy, compliance, explainability, and risk management.
• Maintain governance frameworks for enterprise AI deployments.

Required Qualifications Education

• Bachelor’s or Master’s degree in:
• • Computer Science
  • Artificial Intelligence
  • Machine Learning
  • Software Engineering
  • Data Science
  • Electrical Engineering
  • Related technical discipline

Experience (5-7 Years)

• 5+ years of software engineering experience.
• 3+ years of hands-on AI/ML engineering experience.
• 3+ years leading technical teams or major technical programs.
• Proven experience deploying AI systems into production environments.

Technical ExpertiseProgramming

Strong proficiency in:

• Python
• C/C++

AI/ML Frameworks

Experience with:

• PyTorch
• TensorFlow
• Keras
• Hugging…