Software Engineer Jobs in Richardson, TX

Leads software engineering initiatives within an agile banking technology team. Designs, develops, reviews, debugs, and troubleshoots secure production code; drives responsible AI-assisted development practices; improves automation and operational stability; evaluates architectures and vendors; and promotes modern engineering technologies. The role requires advanced programming, generative AI and machine learning familiarity, distributed systems, cloud platforms, microservices, APIs, databases, containerization, performance testing, and chaos engineering experience.

Leads backend software engineering for secure, scalable, cloud-native microservices applications. Designs and develops Java and Spring Boot solutions, applies domain modeling, builds resilient architectures, reviews code, troubleshoots production issues, and improves automation and operational stability. Champions AI-assisted engineering practices, secure coding, testing, continuous delivery, and technology modernization while mentoring teams and driving engineering best practices.

Leads software engineering efforts for secure, scalable banking technology. Designs, develops, tests, debugs, and reviews production code while guiding teams in responsible AI-assisted development. Applies Java, cloud, microservices, distributed systems, generative AI, performance testing, and chaos engineering practices. Evaluates technical solutions with vendors and internal teams, automates recurring remediation, improves operational stability, and leads engineering communities of practice.

Lead identity and access security architecture, including just-in-time access, zero standing privileges, policy-as-code, adaptive authorization, and Identity-as-a-Service capabilities. Modernize legacy systems into distributed, event-driven platforms while ensuring scalability, operability, compliance, and audit readiness. Define technical strategy and API standards, contribute hands-on to engineering, mentor technical teams, lead cross-domain initiatives, and promote engineering excellence across the organization.

Lead technical vision and architecture across domains, design scalable and operable systems, modernize monoliths into microservices and event-driven platforms, establish API and engineering standards, and mentor technical teams. The role requires hands-on software engineering, cloud and data architecture expertise, cross-divisional leadership, architectural reviews, technical communication, and strategic application of agentic AI coding tools.

Leads strategy and development across multiple software products, applications, and technology portfolios. Designs novel production code, reusable frameworks, and agentic AI-enabled engineering practices with governance for security, validation, auditability, and responsible AI use. Advises senior leadership on complex technology decisions, drives cloud-native and automation adoption, establishes engineering standards and metrics, and influences stakeholders across business, product, and technology teams.

Leads software engineering for secure, stable, and scalable technology platforms. Designs, develops, tests, debugs, and reviews production code; improves application resiliency and operational stability; automates recurring remediation; and promotes secure AI-assisted development practices. Evaluates vendor and internal technical solutions, coaches engineers on responsible AI use, and applies cloud-native technologies, agile methodologies, and CI/CD across the software development lifecycle.

Leads the design, development, and operation of scalable enterprise data products using Databricks and modern data engineering practices. Provides hands-on technical leadership across architecture, implementation, testing, troubleshooting, production readiness, observability, governance, and performance. Partners with architects and product teams to deliver analytical, operational, reporting, and AI-driven solutions. Establishes engineering standards, promotes responsible AI-assisted development, mentors engineers, and improves platform reuse and productivity.

Leads development of secure, scalable, cloud-native full-stack applications using Java, Spring Boot, Python, React, and modern architecture patterns. Designs microservices, REST integrations, authentication solutions, data models, and resilient systems; writes and reviews production code, troubleshoots issues, automates remediation, and promotes zero-downtime delivery. Leads adoption of responsible AI-assisted engineering practices, mentors engineers, drives communities of practice, and supports continuous technology modernization.

Leads architecture and hands-on delivery of complex backend, UI, API, and production AI applications. Owns ADK and LangGraph agentic workflows, establishes engineering standards, drives resiliency and operational readiness, and mentors engineers. Partners across Product, Design, Security, and SRE to deliver secure, scalable systems using Python, React, AWS, FastAPI, databases, CI/CD, and modern software engineering practices.

Leads development of secure, scalable backend and full-stack applications for Asset and Wealth Management. Provides technical direction, writes and reviews production code, optimizes microservices, and promotes AI-assisted engineering practices. Collaborates with architects, designers, distributed teams, wealth managers, and stakeholders to deliver AWS-native solutions. Applies Agile practices, CI/CD, Java and Spring expertise, React-based UI development, relational databases, and high-availability architecture while presenting solutions and guiding technology adoption.

Leads software engineering and AI/ML solution delivery using Java and Python. Designs, builds, operates, and troubleshoots secure, scalable production systems; advances AI-assisted engineering practices; integrates LLM, RAG, and NLP capabilities; develops CI/CD and cloud-native automation; improves observability, reliability, and incident remediation; partners on technical roadmaps; and mentors engineers and AI practitioners.

Provides technical leadership for agile software engineering teams, architecting secure enterprise-scale IBM i systems and driving development, testing, reliability, and modernization. Leads AI-assisted engineering adoption with governance and validation standards, mentors engineers, manages technical debt and resiliency roadmaps, oversees incident troubleshooting, and partners with product and business stakeholders on technical strategy. Requires deep IBM i, DB2 for i, LANSA, integration, debugging, HA/DR, and legacy modernization expertise.

Lead performance and resiliency engineering for high-volume distributed platforms. Responsibilities include load, stress, and soak testing; capacity modeling; performance tuning; observability; alerting; incident triage; root-cause analysis; resiliency patterns; progressive delivery; automated rollback; and optimization of AWS containerized workloads on EKS and ECS. The role also provides technical leadership, mentoring, and cross-team collaboration to improve reliability, scalability, and production readiness.

Leads the design, development, and delivery of secure, scalable software and production AI applications using Python, ADK, and LangGraph. Owns system architecture, API standards, microservices, quality controls, guardrails, testing, resiliency, and operational readiness. Partners with Product, Security, SRE, and engineering teams while driving CI/CD, security scanning, dependency management, and SDLC improvements. Provides technical leadership through design reviews, stakeholder alignment, code reviews, and mentoring.

Lead full-stack engineering for cloud-native, large-scale applications: design and implement frontend (React/TypeScript) and backend (Python) services, author Airflow DAGs, model distributed SQL, deploy and operate on Kubernetes, drive observability with Splunk/Grafana, adopt enterprise AI-assisted development practices, and provide technical leadership across design, delivery, and operational readiness.

Leads architecture, development, and operation of scalable batch and streaming data pipelines on Databricks and Apache Spark. Owns Lakehouse design, cluster configuration, performance tuning, data quality, governance, CI/CD, infrastructure automation, and reusable Python or Java frameworks. Champions secure engineering practices, responsible AI-assisted development, testing, observability, and technical mentorship.

Leads software engineering initiatives focused on application reliability, stability, support, and operational improvement. Designs and develops scalable systems, troubleshoots complex technical issues, analyzes data, and builds monitoring and reporting solutions. Applies AI-assisted development and agentic AI to automate incident detection, remediation, root-cause analysis, alerting, runbooks, and observability. Works with Java or Python, Kubernetes, AWS, monitoring platforms, Splunk, ticketing systems, CI/CD, and agile practices while mentoring engineers and promoting secure, responsible AI adoption.

Lead design, build, and deploy enterprise-grade AI solutions (RAG, agentic systems, LLM integrations). Use AI-assisted development tools daily, architect scalable secure systems on AWS, write production code, own end-to-end outcomes, evaluate vendors, and drive cross-team alignment and automation to improve operational stability.

Leads full-stack software engineering and infrastructure platform development for AI-driven, self-healing data center operations. Designs Java, Python, and Node.js applications, scalable APIs, CI/CD automation, cloud-native platforms, VMware integrations, and infrastructure-as-code workflows. Develops machine learning models for forecasting, anomaly detection, and test classification, integrating them into operational systems for predictive alerts and workload orchestration. Provides technical leadership, mentors engineers, reviews code, and drives firm-wide architecture and technology decisions.

Lead development of secure, scalable Java full-stack applications for mortgage technology. Design, develop, test, troubleshoot, review, and debug production code; improve operational stability through automation and remediation. Drive responsible adoption of enterprise-approved AI-assisted development tools, establish validation and security standards, coach engineers, and evaluate vendor and architectural solutions. Collaborate within agile teams using SDLC, CI/CD, resiliency, and security practices.

Lead software infrastructure engineering for a payment data platform. Responsibilities include deploying and operating ClickHouse clusters, designing scalable AWS infrastructure, developing infrastructure as code, optimizing performance and costs, managing security, automating provisioning and deployments, troubleshooting Linux systems, and maintaining operational tooling. The role also leads architecture efforts, technical problem-solving, engineering community contributions, and adoption of secure, human-in-the-loop agentic AI engineering practices.

Leads software engineering within an agile platform team, providing technical direction, developing and reviewing secure production code, troubleshooting systems, and improving automation and operational stability. Drives responsible adoption of AI-assisted engineering practices, evaluates vendor and startup technologies, promotes secure coding and validation standards, and leads software engineering communities of practice. Requires advanced Java or Python skills, cloud-native experience, CI/CD proficiency, SDLC expertise, and financial-services IT knowledge.

Designs, deploys, maintains, and troubleshoots HPE NonStop payment infrastructure, secure key managers, Etinet servers, and related subsystems. Uses AIOps and AI-assisted practices for incident triage, anomaly detection, automation, documentation, and reliability improvements. Partners with SRE, observability, and cybersecurity teams to govern AI-enabled monitoring, maintain auditability, execute upgrades, and produce operational knowledge such as runbooks and troubleshooting guides.

Leads software and infrastructure engineering for a network test automation platform. Provides technical direction, architects scalable changes, and drives complex programs across cloud, on-premises, data center, operating system, hypervisor, and networking environments. Establishes AI-assisted engineering governance, secure validation practices, automation standards, observability, telemetry, and CI/CD improvements. Collaborates with technical teams, vendors, and other platforms to modernize infrastructure, mitigate risk, and promote reusable engineering frameworks.