AIOps Lead Software Engineer
On-site · Plano, Texas, United States
Job Summary
Lead AIOps-focused software engineering role within JPMorganChase's Consumer & Community Banking Home Lending and Auto Technology team. Responsible for designing and deploying AIOps solutions and automation pipelines to detect, diagnose, and resolve incidents; reducing MTTD/MTTR; leading end-to-end GenAI solutions (including RAG pipelines and vector databases) to enhance reliability, scalability, and performance of the Loan Origination System and related platforms. Collaboration across product, architecture, security, and operations to embed reliability, security, and AI best practices; participation in on-call rotations and postmortems; hands-on coding and mentorship to establish reusable patterns; driving architecture evaluations with external vendors and internal teams; and ensuring compliance, privacy, and model governance for financial services. Demonstrates strong observability, DevOps/SRE fundamentals, cloud experience (AWS), and ability to translate technical complexity for non-technical stakeholders; supports adoption of AI throughout the software development lifecycle and leads communities of practice around modern technologies.
Required Qualifications
- Formal training or certification on software engineering concepts
- 5+ years applied software engineering experience
- 5+ years in software engineering, SRE, DevOps, or platform engineering
- Hands-on experience with AIOps tools and frameworks for model deployment, monitoring, retraining, and lifecycle management
- Experience with GenAI/LLM frameworks (RAG Architectures, vector databases)
- Proficiency in at least one modern programming language (e.g., Python)
- Strong background in observability and monitoring (distributed tracing, logging, metrics, dashboards, alerting)
- Understanding of SRE/DevOps principles (SLA/SLOs, error budgets, MTTR, MTTD, Chaos Engineering)
- Experience with AWS or other public cloud platforms for GenAI workloads
- Experience implementing AIOps solutions using GenAI (anomaly detection, predictive alerting, automated incident response, RCA, self-healing)
- Ability to explain complex technical concepts to non-technical audiences
- Experience introducing AI/ML solutions into engineering teams (creating reusable patterns, providing direction)
- Experience leading evaluation sessions with external vendors or internal teams
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