Top Python Jobs in Houston, TX

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 and manage a team building scalable, resilient distributed and full-stack payment systems. Define technical strategy, drive architecture, deliver cloud-based solutions, mentor engineers, and collaborate with product managers to meet regulatory and performance needs for high-throughput transaction processing.

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.

Lead and mentor engineering teams to design, build, and operate highly available, scalable payment systems (debit network) using cloud-native microservices. Collaborate with product managers, deliver secure cloud solutions, and occasionally write or review code. Drive technical transformation, experiment with new technologies, and support regulatory needs.

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.

Lead enterprise-scale cloud modernization and migration programs to AWS, design end-to-end architectures (including AI agent integration), define AI-native engineering standards, mentor engineering teams, implement IaC and CI/CD, enforce security and governance, and deliver measurable business value through technical strategy and execution.

Lead technical vision and architecture for a cloud-native, low-latency global payments platform. Decompose complex systems, ensure performance/scalability/operability, drive reusable solutions, mentor engineers, evangelize best practices, and apply advanced AI tooling to accelerate development.

Leads the technical vision, architecture, delivery, reliability, governance, and operations of a large-scale risk feature engineering platform. Manages multiple engineering teams and senior leaders, drives Databricks and AWS platform strategy, oversees batch and real-time data systems, and establishes standards for agentic AI-enabled development, security, resiliency, data quality, and regulatory controls. Partners with executives and technology stakeholders to deliver cross-organizational platform adoption and modernization.

Develop and modernize enterprise software by decomposing monoliths into event-driven microservices, building Java and Spring applications, REST APIs, database schemas, stored procedures, and responsive React interfaces. Implement CI/CD, automated testing, Kubernetes deployments, infrastructure automation, observability, distributed tracing, security scanning, and blue-green releases. Support large-scale data migrations, performance tuning, production troubleshooting, and legacy Documentum integrations while producing architecture and technical design documentation.

Lead and mentor a team building high-throughput, resilient distributed microservices and full-stack cloud solutions for global payment processing. Collaborate with product managers, design scalable systems, ensure observability and reliability, and occasionally code, evaluate, and modernize platforms using cloud, container orchestration, and multiple programming languages.

Leads software engineering projects for a global index business platform within investment banking. Develops, tests, reviews, and debugs secure Python and TypeScript production code on the Athena trading and risk platform. Collaborates with quantitative research, trading, sales, structuring, and operations teams to deliver business solutions. Drives responsible adoption and governance of AI-assisted engineering tools, improves SDLC automation, influences platform design, and serves as a technical subject matter expert.

Leads development of resilient, scalable Java and Python services, enterprise integrations, and AI-assisted engineering practices. Architects microservices, Kubernetes deployments, messaging, observability, and backend infrastructure. Builds ML pipeline and feature-store capabilities for fraud and risk models, operationalizes models, and creates agentic AI services with production guardrails, monitoring, governance, and auditability. Mentors engineers, coordinates delivery across stakeholders, and ensures security, performance, testing, and operational requirements.

As a Software Engineer at Citadel, you will build systems for investments, collaborate with researchers, and tackle complex problems.

Lead and deliver secure, scalable cloud-native software solutions; write and review code; drive AI-assisted engineering adoption; evaluate vendors; promote operational stability and engineering best practices.

Lead Software Engineer who designs, builds, and maintains Python services and data/AI pipelines; writes and optimizes SQL; triages and debugs production incidents; develops LLM-powered workflows and agentic systems; implements observability (logging, metrics, traces, alerts); drives adoption of enterprise AI-assisted engineering practices and SDLC automation; and documents system behavior and support procedures.

Lead an agile engineering team to design, build, test, and operate secure, scalable production systems. Drive adoption and governance of AI-assisted development (prompting, agentic engineering) within the SDLC, provide technical guidance, review code, and ensure responsible AI practices and operational stability in trading and risk engineering contexts.