Top Python Jobs in Houston, TX

Leads software engineering for JPMorganChase risk technology, designing, coding, testing, and delivering Python or Java solutions, automation, AI-assisted engineering, data pipelines, and resilient production services. Owns application risk, security, compliance, observability, reliability, remediation, and operational improvements. Collaborates across engineering and product teams, mentors engineers, promotes responsible AI tool adoption, and drives secure, scalable, high-quality software delivery.

Lead and deliver cloud-based, full-stack solutions for a global payments network. Manage a portfolio and team, design distributed microservices, mentor engineers, collaborate with product, and use cloud, container, database, and multi-language technologies to meet regulatory and business needs.

Lead software engineering for secure, scalable applications in Java, Python, and Node.js across AWS and Kubernetes environments. Responsibilities include system design, coding, testing, troubleshooting, code review, SDLC improvement, and technical guidance. The role leads responsible adoption of AI-assisted engineering tools, establishes validation standards, supports automation, and influences application design and technical operations.

Lead software engineering efforts across Java, Python, and cloud-native environments. Design, develop, test, troubleshoot, and maintain secure software using AWS, Kubernetes, and Docker. Provide technical guidance, review code, improve SDLC automation, and promote responsible AI-assisted engineering practices. Influence product design and technical operations while supporting resilient, scalable applications and mentoring teams.

Designs and operates scalable infrastructure for New Relic’s global service mesh, load balancing, ingress data plane, DNS, and CDN systems. The role develops automation and infrastructure-as-code, builds CI/CD pipelines, supports multi-cloud environments, and improves reliability across large-scale services. It requires Go or Python, AWS, networking, Kubernetes, and Terraform experience, with collaboration across product and platform teams.

Leads design, implementation, operation, and production support for scalable corporate technology platforms. Responsibilities include software and data solutions, batch processing, automation, observability, cloud operations, incident and problem management, AI agent and MCP capabilities, secure SDLC practices, roadmap execution, mentoring, and responsible adoption of AI-assisted engineering tools.

Leads site reliability engineering initiatives for enterprise applications and platforms, improving reliability, scalability, performance, security, observability, and service levels. Acts as the primary technical contact during major incidents, drives SLI/SLO and error-budget practices, reduces toil, mentors engineers, and promotes knowledge sharing. Evaluates enterprise-approved AI capabilities for incident response and reliability workflows while enforcing validation, auditability, data-sensitivity, resiliency, and security controls.

Leads full-stack software engineering within JPMorgan Chase’s supply chain technology team. Responsibilities include designing, developing, testing, debugging, and maintaining secure, scalable production systems; advancing AI-assisted engineering practices; automating recurring issue remediation; ensuring application resiliency and security; and evaluating vendor and internal technology solutions. Requires strong software development, cloud-native, agile, financial-services technology, and responsible AI expertise.

Develop and test scalable full-stack cloud applications using JavaScript and Python. Integrate enterprise applications and microservices, manage CI/CD workflows, conduct code reviews, troubleshoot software issues, and collaborate with cross-functional teams to translate business requirements into technical solutions. The role also involves process improvement, client engagement, and supporting digital transformation initiatives.

Lead cross-functional teams to design, build, and deliver scalable enterprise software and products. Own engagement relationships, product roadmaps, architecture (APIs, microservices), CI/CD and quality practices, project planning, and mentoring of junior staff to drive delivery and continuous improvement.

Leads end-to-end design and lifecycle management of hardware platforms supporting internal cloud and PSI environments. Translates requirements into server, board, rack, cooling, and power designs; coordinates OEM, ODM, and JDM suppliers; manages milestones, risks, BOMs, validation, production release, and legacy retirement. Bridges hardware and software stakeholders while applying Linux, scripting, AI-assisted engineering, and infrastructure standards to deliver reliable, secure, auditable solutions.

Builds, configures, monitors, and optimizes applications and cloud infrastructure for availability, reliability, and scalability. Designs deployment strategies, CI/CD pipelines, infrastructure and network as code, observability practices, and SLO-based alerting. Troubleshoots complex issues, performs incident and post-incident analysis, and improves reliability proactively. Guides peers in SRE practices and uses authorized AI capabilities to accelerate triage and identify reliability risks while validating recommendations and protecting sensitive operational data.

Leads software engineering within JPMorganChase’s Corporate Data and Analytics team. Responsibilities include designing, developing, testing, debugging, and supporting secure, scalable production systems; reviewing code; improving operational stability; automating recurring remediation; and evaluating architectural solutions. The role also drives responsible adoption of AI-assisted engineering tools, coaches teams on secure validation practices, manages stakeholders and vendors, and supports data ingestion, management, and analytics initiatives.

Develop and modernize Credit Risk technology applications using Java or Python, SQL, and Databricks. Design, build, test, debug, and maintain secure, scalable production software; create architecture artifacts; analyze large datasets; troubleshoot complex systems; and improve coding practices and system architecture. Use authorized AI-assisted development tools responsibly, validate generated outputs, and contribute to engineering standards and automation.

Leads development of secure, scalable software for a distributed multi-tenant platform, including APIs, data ingestion, pipelines, dashboards, and isolated AWS deployments. Designs and operates cloud-native Kubernetes workloads, promotes automation and AI-assisted engineering practices, and champions security, privacy, and supply-chain controls. Evaluates architectures, mentors teams, improves operational stability, and supports platform delivery across regulated environments.

Leads development of secure, scalable software solutions within an agile financial-services environment. Responsibilities include designing, coding, testing, debugging, reviewing production code, improving application stability through automation, applying AI-assisted engineering practices responsibly, and evaluating vendor and architectural solutions. The role requires advanced Python expertise, cloud-native experience, SDLC proficiency, software security knowledge, and familiarity with banking technology systems.

Administer and improve global block, file, and object storage across on-premises and cloud environments. Manage performance, capacity, resiliency, replication, backup, disaster recovery, incident response, root-cause analysis, and operational automation. Build observability and AI-assisted AIOps workflows with validation, guardrails, auditability, and human review. Maintain runbooks, SLOs, SLIs, error budgets, and on-call readiness while partnering with infrastructure and application teams.

Leads design, development, testing, troubleshooting, and operational stability for secure full-stack software solutions. Develops Java and Scala statistical algorithms, React-based applications, microservices, REST APIs, and cloud-native services using AWS, Hadoop, Databricks, and Kubernetes. Reviews code, improves automation and resiliency, performs unit and integration testing, and promotes responsible AI-assisted engineering practices, secure coding, and compliant validation across an agile team.

Administer and improve enterprise block, file, and object storage across on-premises and cloud environments. Responsibilities include performance and capacity management, incident response, root-cause analysis, automation, backup and recovery, resiliency testing, observability, runbook development, and on-call operations. The role also implements AI-assisted infrastructure analysis and AIOps capabilities with strong validation, security, auditability, and human oversight while partnering with infrastructure, network, operating system, database, and application teams.

Develop high-performance research platforms and tools that bring trading strategies to life. Work in small teams to design, build, and deploy resilient systems using distributed computing, NLP, and machine learning to solve large-data problems in finance.

Lead engineer responsible for designing, building and operating scalable Big Data/ETL pipelines and production services on AWS. Drive automation (including LLMs/agents), SRE practices, security and data accountability, monitoring/alerting, incident management, and cross-team coordination. Champion AI-assisted engineering, remediate control/security findings, and improve reliability, performance, and operational efficiency.

Lead teams and projects to design, build, and operate scalable, highly available payment systems. Mentor engineers, collaborate with product managers, deliver cloud-native full‑stack solutions using microservices, containers, databases, and AWS/Azure/GCP technologies, and occasionally write or review code.

Develops and maintains Python and LabVIEW automation for production testing of high-speed optical transceivers and components. Integrates optical and electronic test instruments, debugs optical, electrical, and thermal systems, troubleshoots manufacturing failures, and improves yield and reliability. Creates SOPs and training materials, trains operators and technicians, maintains test documentation and revision control, and collaborates with R&D, QA, manufacturing, and IT teams. Requires occasional international travel for deployments and training.

Tests high-speed optical transceiver interoperability from 400G to 1.6Tbps, installs and operates high-density network switches, conducts communication link testing, troubleshoots failures, identifies root causes with cross-functional teams, supports production traffic testing, and generates test reports.

Administers Linux servers and Proxmox VE infrastructure, including clusters, virtual machines, containers, storage, backups, monitoring, security, and disaster recovery. Automates administration with scripting and configuration management, troubleshoots infrastructure issues, maintains documentation, supports critical incidents, and collaborates with IT teams in an onsite manufacturing environment. Participates in on-call coverage and planned maintenance.