Principal Software Engineer — AI & Data Engineering
JPMorgan Chase & Co. (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 45–85 LPA
Posted on 15 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, deploy, operate, and continuously improve production AI-native services, agentic systems, APIs, automation services, data pipelines, and cloud-native components.
- Architect and govern agent-enabled AI workflows to improve delivery speed, code quality, and operational outcomes at scale, ensuring validation, security, resiliency, and reuse.
- Own observability, monitoring, incident response, performance tuning, and cost optimization for AI and data engineering systems while leading design and code reviews and mentoring peers.
Minimum Requirements
- 7+ years of applied software engineering experience with formal training or certification.
- Proven hands-on experience architecting, developing, deploying, operating, and debugging production AI systems, agentic services, and cloud-native workloads.
- Strong proficiency in Python and experience with AI/ML frameworks such as LangChain, LlamaIndex, PyTorch, or Hugging Face.
- Deep experience with Google Agent Development Kit (ADK), Model Context Protocol (MCP), or equivalent agentic development frameworks including production operation and secure tool exposure.
Ideal Candidate Profile
- Experienced in designing and leading adoption of AI-enabled development workflows incorporating human-in-the-loop validation, auditability, and secure data handling at scale.
- Skilled in embedding enterprise knowledge into models and agents using vector stores, retrieval pipelines, and evidence-based response generation.
- Capable of evaluating AI models and agents for task success, factuality, compliance, latency, cost, and operational health including monitoring for drift and anomalies.