Senior AI & Data Systems Engineer

Next Frontier Capital; Houston (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

JPMorgan Chase, a global financial leader, seeks a Principal Software Engineer to architect scalable, secure AI-enabled systems within the Corporate sector. You will drive design, production-grade code, and cross-team collaboration to deliver trusted market-leading technology products.

You will design agentic AI workflows, implement LLM-based solutions, and mentor engineers while upholding regulatory standards and best practices across the software lifecycle.

Qualifications

• Formal training or certification on software engineering concepts and 7+ years applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability at enterprise scale.
• Hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments.
• Expert in one or more programming languages, particularly Python and/or Java.
• Advanced knowledge of software application development and technical processes, with considerable depth in cloud, AI/ML, data engineering.
• Experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal).
• Advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
• Practical cloud-native experience (AWS, Azure, or GCP).
• Ability to present and effectively communicate with senior leaders and executives.

Responsibilities

• Architects and implements complex, scalable engineering frameworks and solutions using modern software design principles.
• Develops secure, high-quality production code for data-intensive applications and platforms, and reviews and mentors other engineers.
• Creates durable, reusable software frameworks and patterns that are leveraged across teams and functions.
• Designs and governs agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls appropriate for regulated financial services environments.
• Establishes engineering standards for LLM-based applications — RAG pipelines, embedding workflows, vector store integrations, and model serving — ensuring safety, observability, and reproducibility at scale.
• Drives adoption of advanced technical methods and practices aligned with the latest industry standards and product development methodologies.
• Serves as the function's go-to subject matter expert in one or more areas of focus within data engineering, platform architecture, or AI systems.
• Advises cross-functional teams on technological matters within your domain of expertise.
• Influences leaders and senior stakeholders across business, product, and technology teams on technical strategy and direction.
• Architects and governs agentic AI-enabled engineering workflows with guardrails for validation, security, resiliency, and reuse across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities.

Skills

Python

Java

LLM-based systems

Data engineering

Cloud platforms

System design

Production code

Communication with executives

Agile methodologies

Education

Bachelor's degree in CS/Engineering

Tools

Dynatrace

Splunk

Grafana

Kafka

Redis

Databricks/Snowflake

Job description

JPMorgan Chase, a global financial leader, seeks a Principal Software Engineer to architect scalable, secure AI-enabled systems within the Corporate sector. You will drive design, production-grade code, and cross-team collaboration to deliver trusted market-leading technology products.

You will design agentic AI workflows, implement LLM-based solutions, and mentor engineers while upholding regulatory standards and best practices across the software lifecycle.