Staff Engineer – GenAI Platforms & Agentic SDLC

Qualcomm India Private Limited seeks a Staff Engineer in Hyderabad to design, develop and scale GenAI platforms, agentic workflows and AI-native software development lifecycle (SDLC) capabilities across CPSE. The role aims to move AI initiatives from pilots to production-grade, enterprise-scale use across engineering teams.

Responsibilities

• Build reusable AI skills, agents, MCP servers, orchestration frameworks and integrations with internal platforms, enterprise data sources, and development, testing and operational systems.
• Develop reusable prompts and workflows, establish validation for their quality, accuracy and robustness, and drive standardization across teams and business units.
• Operationalize QGenie-based workflows for CPSE, prioritize high-impact automation opportunities and turn existing engineering workflows into scalable AI-driven solutions.
• Implement agent-driven workflows for coding, code review, testing, release and deployment, debugging, root-cause analysis, production monitoring and operations.
• Establish AI governance, compliance, observability and decision traceability frameworks, with attention to production security, auditability and reliability. Partner with QGenie teams, business units and GEO organizations to align priorities and expand adoption across regions.

Qualifications

• The posting lists minimum degree-and-experience alternatives: a relevant bachelor’s degree and 4+ years of software engineering or related experience; a relevant master’s and 3+ years; or a relevant PhD and 2+ years. It also specifies 2+ years with a programming language such as C, C++, Java or Python.
• A separate required section calls for a bachelor’s or master’s degree in Computer Science, Engineering or a related field and 8–12 years in software engineering or platform development. Required hands-on experience covers distributed systems, cloud platforms, APIs, AI/ML systems, LLMs or GenAI frameworks, developer tools, CI/CD and SDLC processes, plus a record of building scalable platforms used across teams.
• Preferred experience includes agentic systems, workflow orchestration or AI copilots; prompt engineering, evaluation frameworks and LLM integrations; observability and production AI systems; and enterprise-scale AI adoption or platform engineering. The role also calls for architectural leadership, cross-functional impact, mentoring and data-driven evaluation of AI adoption.