Manager - Software Engineering

UPS • Dallas, TX

5h

About The Position

MANAGER, SOFTWARE ENGINEERING Applies the principles of software engineering to design, develop, maintain, test, and evaluate computer software that provide business capabilities, solutions, and/or product suites. Provides systems life cycle management (e.g., analyses, technical requirements, design, coding, testing, implementation of systems and applications software, etc.) to ensure delivery of technical solutions is on time and within budget. Researches and supports the integration of emerging technologies. Provides knowledge and support for applications’ development, integration, and maintenance. Develops program logic for new applications or analyzes and modifies logic in existing applications. Analyzes requirements, tests, and integrates application components. Ensures that system improvements are successfully implemented. May focus on web/internet applications specifically, using a variety of languages and platforms. Defines application complexity drivers, estimates development efforts, creates milestones and/or timelines, and tracks progress towards completion. Is accountable for the performance and results of a team or multiple teams. Coordinates work across the organization to ensure effectiveness. Makes decisions about the workforce – e.g., who to hire, how to develop them, and how to reward them. Focus is on connecting/integrating processes and people. Directly manages subordinate supervisors or a team of employees who apply conceptual and theoretical expertise. Has accountability for the performance and results of a team within own area of specialty. Adapts departmental plans and priorities to address resource and operational challenges. Typically focuses on an annual time horizon. Provides technical guidance to employees, colleagues and/or customers. Decisions and problem solving are guided by policies, procedures and department plan; receives guidance from manager. Agile Engineering Best Practices Identifies and recommends improvements to the AI software development lifecycle and best practices in agile engineering. Provides input into various software development strategies (e.g., unit testing, acceptance testing, continuous delivery and integration, release and deployment for frequent and reliable release), providing the case for using agile vs. traditional methodologies. Develops the roadmap and guidelines for tailoring agile practices to a complex and dynamic software development project. Project Management Prioritizes multiple project plans, making final decisions about priorities, timing and resources. Keeps abreast of the progress of multiple projects within a program or across the department; coaches project managers to adjust priorities or timelines as needed. Monitors resource usage across projects or programs, identifying areas or synergy or redundancy and looking for ways to optimize efficiency. Troubleshooting Provides guidance and expertise to analyze data and patterns and assess the root cause of complex, non-routine problems. Collaborates with others across disciplines to brainstorm and execute solutions to the most complex, uncommon problems. Guides the execution of solutions for complex, non-routine issues; redirects solution implementation if desired results were not originally met. Application Development/Programming Identifies areas for improvement and develops innovative enhancements using available software development tools following design requirements of customer. System and Technology Integration Interprets internal/external business challenges and recommends integration of the appropriate systems, applications and technology to provide a fully functional solution to a business problem. Technology Advising/Consulting Exceeds customers’ expectations by listening for unexpressed needs; connects customer needs to relevant service offerings and new technology. Leads others in resolving technical issues in a timely manner; follows up with customers to ensure satisfaction. Partners with the business to integrate new technologies into business solutions; creates and communicates a vision of the technology requirements for the future state of the business. Additional: Team Leadership & Mentorship: Lead a cross-functional team of ML Engineers and Software Engineers. Foster a culture of technical excellence, continuous learning, and psychological safety. AI Strategy & Execution: Translate complex product requirements into technical roadmaps. Balance short-term delivery (MVPs) with long-term R&D and foundational model improvements. System Architecture: Oversee the design of scalable ML pipelines, from data ingestion and feature engineering to model deployment (MLOps) and monitoring. Cross-Functional Collaboration: Partner with Product Managers, Data Scientists, and Ethics/Compliance teams to ensure AI solutions are impactful, feasible, and responsible. Quality & Governance: Establish standards for code quality, testing (including model validation), and CI/CD for ML. Ensure data privacy and security standards are met.

Requirements

• Strong tech lead experience with people leadership).
• Strong backend engineering skills (Python/TypeScript/Java/Go).
• Production experience with LLMs and agent frameworks (LangChain, LlamaIndex, Semantic Kernel, custom orchestrators, etc.).
• Experience building API-driven systems and integrating with external tools/services.
• Strong understanding of Prompting and structured outputs, RAG and embeddings, Tool calling, planning, routing and Evaluation methods for LLM systems
• Experience deploying to cloud (AWS/GCP/Azure), containerization, CI/CD.
• Excellent written and verbal communication skills
• Bachelor’s degree in product design, technology or related field
• Must be currently located in the same geographic location as the job or willing to relocate yourself

Responsibilities

• Lead, hire, mentor, and grow a team of AI agent engineers and applied ML engineers.
• Own delivery of agent-based features from concept → prototype → production.
• Drive technical architecture for: Agent orchestration (single-agent + multi-agent systems) Tool calling and function execution Retrieval-Augmented Generation (RAG) Memory, state, and context management Guardrails, policy enforcement, and safety controls
• Partner with Product, Design, Data, Security, and Legal teams to define requirements and success metrics.
• Establish best practices for: Prompt engineering standards Agent evaluation and testing (offline + online) Monitoring, tracing, and observability Cost optimization (token usage, caching, model selection)
• Ensure production reliability (latency, uptime, failure handling, fallback behavior).
• Review code and design docs; provide technical leadership and unblock engineers.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager