Lead Software Engineer - Java / Python / AWS / AI/ML
Salary not listed • Plano, TX, United States • Full-time
Posted 24d ago
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Job Location
Plano, TX, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
As a Lead Software Engineer within Commercial & Community Banking, you will be a core technical contributor responsible for enhancing, building, and delivering trusted market-leading technology products in a secure, stable, and scalable way. You will drive the design and development of creative full-stack software solutions, including building and implementing AI-driven capabilities such as LLM-based services and integrations into business workflows. A key aspect of this role involves driving team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while also architecting and delivering cloud-native microservices and APIs.
Responsibilities
- Design and develop full-stack software solutions.
- Build and implement AI-driven capabilities, including LLM-based services, orchestration, and integrations.
- Drive team adoption of AI-assisted engineering practices for improved code quality, delivery speed, and operational outcomes.
- Leverage AI coding assist tools to improve code quality, delivery speed, and productivity.
- Apply knowledge of SDLC tools, including AI-assisted development and automation capabilities.
- Architect and deliver cloud-native microservices and APIs, ensuring scalability, resilience, and security.
- Identify and automate solutions for recurring operational issues.
- Communicate project status clearly and manage priorities.
- Collaborate within a Scrum team and participate in Agile ceremonies.
- Code in Java, AWS ECS, EKS, and Postgres.
- Utilize AI agents (CoPilot, Claude) to improve quality and delivery timelines.
Requirements
- 5+ years of applied experience in Software Engineering.
- Strong system design, application development, and operational stability skills.
- Hands-on experience using enterprise-authorized AI-assisted software development tools and ability to validate AI-generated outputs.
- Understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling.
- Ability to influence product design, application functionality, and technical operations.
- Hands-on experience with Large Language Models (LLMs) and generative AI use cases (e.g., RAG, agents, prompt/tool orchestration, evaluation/guardrails).
- Familiarity with AI/ML frameworks and ecosystems (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).
- Experience with distributed systems and at least one major cloud platform (AWS, GCP, or Azure).
- Expertise in microservices, RESTful APIs, and data technologies (relational and/or NoSQL).
- Practical experience building cloud-native systems (event-driven architectures, streaming, service mesh).
- Familiarity with DevOps practices and tools for continuous integration and deployment.
- Advanced Java proficiency.
- Working knowledge of Python for AI/ML implementations is a plus.