Lead Infrastructure Engineer (IOT/Edge Computing)

Join us to shape the future of infrastructure engineering with a focus on IoT and edge computing. You will partner with talented colleagues globally to solve complex challenges and deliver measurable outcomes across our technology landscape. At JPMorganChase, you’ll find a culture of inclusion, respect, and opportunity—where your expertise is valued, your voice influences direction, and continuous learning is expected and supported. Bring your passion for modern infrastructure and help us innovate at scale.

As a Lead Infrastructure Engineer – IoT and Edge Computing within our Infrastructure Engineering team, you will set technical direction and lead delivery for critical IoT and edge initiatives. You will architect and implement resilient, secure, and observable solutions; guide engineering standards and operational excellence; and serve as a senior partner to product, engineering, and stakeholders. You will mentor engineers, drive cross-platform alignment, and ensure solutions meet compliance, auditability, and service reliability expectations.

Job Responsibilities

• Lead architecture and execution of complex infrastructure engineering initiatives spanning IoT, edge computing, and real-time data systems
• Own technical direction for one or more IoT/edge domains (connectivity, edge runtime, device onboarding, telemetry/observability, identity, lifecycle management) and contribute to multi-quarter roadmaps
• Drive multiple workstreams or large, high-impact projects, coordinating dependencies across global teams and platforms
• Partner with other platforms to design and implement changes that modernize technology processes, reduce risk, and improve reliability and performance
• Provide hands-on engineering leadership for design, development, automation, integration, and technical troubleshooting of high complexity; unblock teams and accelerate delivery
• Set and enforce engineering standards (reference architectures, patterns, reusable components, guardrails, operational readiness, SLO/SLA alignment)
• Evaluate upstream/downstream system and data implications, advise on mitigations, and ensure changes are resilient, secure, and compliant
• Lead stakeholder management across technology and business partners; communicate tradeoffs, decisions, and progress with clarity and accountability
• Champion a culture of diversity, opportunity, inclusion, and respect, including mentorship, coaching, and feedback that grows others
• Partner with engineering and product teams to ensure remediation and permanent closure of issues, identify trends, and drive systemic product improvements
• Lead incident/problem/change management outcomes: facilitate root cause analysis, define corrective actions, and drive prevention through automation and control enhancements
• Demonstrate a high aptitude for learning and teaching, including sharing best practices as new features and products are released
• Partner with subject matter experts to understand and deliver business value through IoT and edge solutions
• Use enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements
• Apply reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations

Required Qualifications, Capabilities, and Skills

• Formal training or certification in infrastructure engineering concepts
• Extensive applied experience in infrastructure engineering, including IoT, edge computing, and/or real-time data systems, with demonstrated ownership of production outcomes
• Deep knowledge of network infrastructure, edge computing, and IoT device connectivity (e.g., MQTT, CoAP, LoRaWAN, 5G/WiFi standards)
• Proven expertise in multiple areas of infrastructure engineering such as hardware, networking, databases, storage, deployment, integration, automation, scaling, resilience, and performance assessments
• Demonstrated ability to lead architecture decisions, drive technical consensus across teams, and influence platform direction/standards
• Strong understanding of workplace infrastructure design and human usability patterns
• Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations
• Proficiency in at least one infrastructure technology and scripting languages (e.g., Python)
• Knowledge of cloud infrastructure and multiple cloud technologies, with ability to operate in and migrate across public and private clouds
• Strong leadership and team coordination skills, including mentoring and guiding engineers through delivery and operational challenges
• Familiarity with large distributed systems, including compute, databases, messaging, observability, and telemetry
• Strong knowledge of incident, change, and problem management processes and controls
• Understanding of data-driven decision making and practical metrics/SLO thinking
• AWS certification(s)
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity

Preferred Qualifications, Capabilities, and Skills

• Certifications in Kubernetes, Azure, GCP, or Terraform
• Experience with building or industrial automation protocols (e.g., BACnet, Modbus) or embedded systems communication protocols (e.g., I2C, UART, BLE GATT)
• Knowledge of contemporary metadata schemas (e.g., Brick, Project Haystack, RealEstateCore) and frameworks for building/querying knowledge graphs (e.g., RDF, SPARQL, SHACL)