Principal Software Engineer – Generative AI & Agentic Platforms
Infosys · infosys.com
BengaluruLead / Manager7+ yrs
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The job in short
Principal software engineer on generative AI and agentic platforms.
PythonJavaJavaScriptC++ReactAngularVueAWSAzureGCPGenAIGenerative AI
Details
- Found
- 7 d ago · posted 2026-10-30
- Location
- Bangalore
Full description
About the role
We are seeking a Principal Engineer with deep expertise in Generative AI (GenAI) and agentic systems, focused on embedding intelligent agents and AI driven workflows directly into the Software Development Life Cycle (SDLC). This role will help advance automation, decision making, and developer productivity across engineering platforms.
Responsibilities
Act as a hands on technical leader within an Agile environment, promoting engineering best practices and effective collaboration.
•Contribute thought leadership to solution design and architectural discussions, ensuring alignment with enterprise architecture standards.
•Design, develop, and implement modern, architecturally sound software components, tools, and applications to support strategic business objectives.
•Serve as a peer leader and mentor, fostering a culture of innovation, accountability, and technical excellence.
Technical requirements
7+ years of hands-on software engineering experience delivering commercial software products.
•Demonstrated ability to lead, influence, and mentor senior software engineers.
•5+ years of experience working with big data—querying, analyzing, and managing large scale datasets.
•Proficiency in multiple programming languages, including at least one modern front end framework (Angular, React, or Vue), and languages such as Python, Java, JavaScript, Ruby, Go, C/C++.
•Strong cloud experience with AWS, Azure, or GCP, including handling sensitive and regulated data.
•Hands on experience with LLM frameworks and services (e.g., OpenAI, AWS Bedrock/SageMaker, Hugging Face, LangChain/LangGraph).
•Deep understanding of RAG techniques, embedding models, and vector databases.
•Familiarity with LLM deployment, prompt engineering, fine tuning, evaluation, and guardrail techniques.
•Strong understanding of responsible AI, privacy, and security considerations for production AI systems.
Preferred skills
Foundational ->Artificial Intelligence->Responsible AI by Design,Technology->AI-AI Engineering->LLMOps
Education
Bachelor of Engineering
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