Software Engineering Lead

United States Cold Storage, Inc.•Conshohocken, PA

14h•$140,000 - $160,000•Hybrid

About The Position

Software Engineering Lead Architect the systems that coordinate the movement of food at national scale. Who We Are: United States Cold Storage owns and operates one of the most complex temperature-controlled logistics networks in North America. Every day, our systems coordinate the storage and movement of food at national scale across a network of state-of-the-art distribution centers, including multiple highly automated warehouse facilities. We continue to advance our core warehouse and logistics platforms. Our current focus is on modular, event-driven, API-first and cloud architectures. We continue to enhance reliability and accelerate engineering productivity by strengthening our SRE and AI practices. This is a large investment in innovation to continue to drive operational excellence at our facilities. If you want to build durable systems that operate in the physical world at scale, this is that opportunity. The Role: We are hiring a Software Engineering Lead to own the architecture and delivery of our logistics solutions as we continue modernizing toward distributed, Azure-native systems. You will write production code. You will shape architecture. You will be accountable for reliability. This is not a role building internal tooling for a small team. This is for building production software supporting real-world operations with uptime expectations. Why this role is different: This is a modernization journey, not a greenfield startup. You will operate within real operational constraints while improving the system every day. You will help modernize the technology backbone of a company that moves food every day. You will shape architecture of durable systems that operates under real constraints. The Kind of Problems You’ll Solve: Coordinating distributed logistics workflows across facilities. Designing systems that remain reliable under operational load. Integrating external partner APIs without compromising internal stability. Embedding observability into systems from day one. Modernizing legacy components without interrupting live operations. This role is for someone who prefers substance over hype. This role requires engineering depth, architectural discipline, and comfort operating in environments where uptime matters. Operational Context: This role is primarily technical and office-based, with occasional interaction in operational environments depending on system needs.

Requirements

10+ years of software engineering experience, including 5+ years in architectural roles.
Experience supporting mission-critical production systems.
Expert proficiency in Python, including data processing and optimization libraries.
Strong experience across multiple programming languages, database design and query optimization, and containerization technologies.
Experience designing and implementing REST APIs, webhooks, and event-driven architectures.
Working knowledge of modern front-end technologies.
Strong experience with Azure-native services such as Azure Functions, Azure SQL Database, Data Factory, and Logic Apps.
Experience building and maintaining CI/CD pipelines.
Experience embedding logging, monitoring, alerting, and observability into applications.
Ability to communicate complex architectural decisions to both technical and business audiences.
Bachelor’s degree in computer science or related field, or equivalent experience.

Nice To Haves

Supply chain or logistics software.
Optimization algorithms and decisioning systems.

Responsibilities

Definition and evolution of the technical architecture for the logistics platform.
Architectural standards for scalability, testability, observability, and resilience.
Design of REST APIs, webhooks, and event-driven patterns supporting distributed workflows.
Cross-team alignment with platform, infrastructure, and security partners to ensure high availability and disaster-recovery–first design.
Hands-on design and development of production-grade code.
Technical quality through leading code reviews and architectural reviews.
Automated testing standards, tooling, and enforcement.
CI/CD-aligned SDLC pipelines from design through deployment.
Proof-of-concepts with business stakeholders and drive successful ideas into production.
Design and implementation of integrations with warehouse management systems, logistics partners, and carrier technologies.
Data consistency, performance, and reliability across system boundaries.
Collaboration with data science and analytics teams to operationalize predictive and optimization models.
Embedding of routing, consolidation, and carrier-selection logic into production systems.
Observability, measurement, and maintainability of models running in live environments.
Mentorship and technical guidance for a small team of software development and QA engineers.
Clear communication of architectural decisions and tradeoffs to engineers and senior leadership.
Evaluation and adoption of tools that improve developer productivity, system visibility, and operational resilience.
Responsible use of Gen-AI tooling where it meaningfully improves engineering throughput or quality.