Alvys

• Architect, build, and scale ML models and AI-driven solutions using frameworks like TensorFlow or PyTorch, ensuring they are optimized for real-world transportation logistics. • Lead the full lifecycle of AI features, from initial data engineering and model training to deployment within a cloud-native Azure environment. • Integrate predictive models and intelligent reporting systems into the core .NET/C# and CosmosDB ecosystem, ensuring seamless communication between the backend and AI services. • Operational Excellence (MLOps): Implement and maintain robust CI/CD pipelines and monitoring via Azure Monitor to ensure model performance, reliability, and fairness in production. • Partner with Product Managers to translate complex logistics challenges into technical roadmaps and actionable AI innovations.

• Product ownership (outcome-driven): Own a product area end-to-end, including problem framing, implementation, rollout, and iteration. • Technical leadership: Lead multi-person projects, write and review design docs, and make sound architectural decisions. • Operational excellence: Build systems that are observable and reliable, participate in incident response, and drive post-incident improvements. • Cross-functional collaboration: Partner closely with Product, Design, and operational stakeholders to ship high-leverage workflow improvements. • Mentorship: Mentor engineers through code reviews, pairing, and setting high standards for quality and product thinking. • Complexity reduction: Identify opportunities to simplify architecture, workflows, and UX to improve both customer experience and developer velocity.

• Monitor real-world usage patterns and production signal • Investigate unexpected behaviors, workflow gaps, and small feature misalignments • Partner with Support and Customer Success to understand impact • Implement targeted fixes and workflow hardening • Own quality for your product area end-to-end • Design, implement, and maintain automated test suites • Improve dashboards, alerts, and incident response workflows • Partner closely with Product Engineering, Product, Design, Customer Success, and Support

• Own a product area end-to-end, including problem framing, implementation, rollout, and iteration. • Lead multi-person projects, write and review design docs, and make sound architectural decisions. • Build systems that are observable and reliable, participate in incident response, and drive post-incident improvements. • Partner closely with Product, Design, and operational stakeholders to ship high-leverage workflow improvements. • Mentor engineers through code reviews, pairing, and setting high standards for quality and product thinking. • Identify opportunities to simplify architecture, workflows, and UX to improve both customer experience and developer velocity.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Alvys is building the operating system for modern freight with a multi-tenant SaaS platform that streamlines day-to-day transportation operations. As a Senior Product Engineer , you will be a senior individual contributor who owns meaningful product areas end-to-end: - Shaping what we build - How we build it - Whether it worked for customers This role is designed for engineers who want to sit at the intersection of engineering execution, product judgment, and operational ownership, and who are excited to build with AI as a first-class part of the workflow. We are moving quickly toward an AI-first operating model across the company. On the engineering side, we have shifted from a traditional model with many handoffs to a product engineering model where engineers are accountable for outcomes and leverage AI to accelerate delivery. As a Senior Product Engineer , you will use AI to: - Move faster while keeping quality high - Be accountable for outcomes - Utilize AI tools for implementation, debugging, and test generation - Review and harden AI-generated code with strong engineering judgment - Iterate quickly with customer feedback and production signal - Contribute to evolving team practices as the AI toolchain changes In this role, “senior” is measured by impact , which includes: - Owning customer and business outcomes - Influencing product direction through strong problem framing and tradeoffs - Shipping and operating production systems with a reliability mindset Qualifications - 5+ years of professional software engineering experience, with ownership of production systems - Strong proficiency in at least one modern programming language (C#, TypeScript, Java/Kotlin, etc.) - Full-stack capability: comfortable working end-to-end (API → data → UI) - Experience building and operating production software, including debugging, monitoring/alerting, and performance tuning - Experience with data stores in production (relational and/or NoSQL) - Experience with at least one major cloud provider (Azure, AWS, or GCP) - Strong collaboration and communication skills with cross-functional partners (Product, Design, and operations stakeholders) Requirements - AI-first product engineering experience: actively used AI to ship product faster - Championing AI adoption: experience introducing AI tooling to a team - Strong React proficiency: experience building complex, data-heavy UIs in React and TypeScript - Design systems experience: building or operating within a design system - Experience building and operating large-scale systems, focusing on reliability, performance, and cost - Experience with observability and operational rigor (dashboards, alerting, incident response) - Experience with .NET/C#, CosmosDB, Postgres, Elastic Search, and modern web APIs - Experience mentoring engineers and raising engineering quality through design reviews and code reviews - Experience in logistics or transportation software is a plus Benefits - Revolutionizing transportation logistics - Balancing innovation with sustainability - Fostering a culture of reliability and performance Company Description Alvys is on a mission to revolutionize transportation logistics. We are evolving from a delivery organization into a product engineering organization —one that blends technical excellence with deep product context and financial accountability. - We measure success by impact, not output - We think like operators, not just builders

• Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications. • Own the design and evolution of our Snowflake architecture. Lead the implementation of Snowflake Cortex for AI/ML workloads, including semantic models and LLM agents. • Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale. • Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter. • Think holistically about the data estate. Reduce complexity through modularity and well-defined service boundaries (e.g., Medallion Architecture). • Serve as the go-to expert for emerging data trends. Mentor engineers and partner with Product and Design to translate complex business logic into automated deliverables.

Industry Insight Transportation logistics is the foundational industry that powers everything we rely on daily, yet it remains a complex and fragmented domain ripe for technological revolution. The US transportation logistics industry alone is an $800 billion market. Alvys is not just participating in this change; we are driving it as the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to truly transform this essential sector. Your role will be at the forefront of automating and standardizing a sector that moves trillions of dollars' worth of goods annually, predominantly by truck, but still lacks modern tools and solutions. Your leadership will help bridge this gap, bringing innovative technologies to a traditionally underserved and mission-critical industry. About Alvys Alvys is the fastest-growing Transportation Management System (TMS) in history, uniquely positioned to dominate and truly revolutionize the $800 billion US transportation logistics industry. We're not just iterating on old tools; we're building a world-class, multi-tenant SaaS platform from the ground up to automate, standardize, and transform this essential sector. Join us to apply your technical vision to one of the economy's most mission-critical and underserved markets, making a massive, tangible impact on the movement of global goods. This is where industry experience meets cutting-edge technology to create the undisputed market winner, and you will be a core part of that journey. About the Role As a Staff Data Engineer, you will be the primary architect of our data ecosystem. Alvys is shifting toward a Snowflake-centric data architecture to power our next generation of logistics intelligence. You aren't just building pipelines; you are defining our LLM-based data strategy, enabling large-scale ML model deployment, and leveraging Snowflake Cortex to turn fragmented logistics data into actionable AI-driven products. This is a high-visibility, 'player-coach' position. You will work closely with leadership to ensure our data infrastructure supports real-time operational needs today while scaling for the AI-first logistics world of 2026 and beyond. Our Tech Stack - Data Platform: Snowflake (Warehouse, Cortex AI/ML, Semantic Models, LLM Agents) - Data Pipelines: dbt, Fivetran, Reverse ETL (Census) - AI/ML: Snowflake Cortex, OpenAI, Azure Cognitive - Backend/Infra: .NET/C#, Python, Azure Ecosystem, GitHub Actions Key Responsibilities - Define and implement the strategy for LLM-based data products, including data preparation, semantic layer design, and embedding pipelines for RAG-based applications. - Own the design and evolution of our Snowflake architecture. Lead the implementation of Snowflake Cortex for AI/ML workloads, including semantic models and LLM agents. - Design and maintain reliable, performant ELT/Reverse ETL pipelines. Ensure our multi-tenant SaaS data remains isolated, secure, and performant at scale. - Build and operationalize pipelines for large-scale ML and LLM model development, moving from POC to production-grade deployment within the Snowflake perimeter. - Think holistically about the data estate. Reduce complexity through modularity and well-defined service boundaries (e.g., Medallion Architecture). - Serve as the go-to expert for emerging data trends. Mentor engineers and partner with Product and Design to translate complex business logic into automated deliverables. The Experience You Have - 7+ years of experience in Data Engineering with a proven track record of delivering mission-critical data platforms. - Deep proficiency in Snowflake (Data Modeling, Query Optimization, Security, and Cortex AI functions). - Expert-level skill in SQL and Python. Extensive experience with dbt and modern orchestration (Airflow/Dagster). - Demonstrated experience building pipelines for ML or LLM-based applications, including feature engineering and model deployment. - Competency in Azure (preferred) or other major cloud providers, including CI/CD and infrastructure-as-code principles. - Experience driving cross-team consensus on architectural decisions and mentoring junior/mid-level engineers. The Way You Work - Ownership: You take end-to-end responsibility. If it’s in production, it’s yours—from the initial schema design to the final dashboard latency. - Pragmatism: You believe technical debt is a strategic choice. You choose solutions that scale and solve real problems over theoretical "perfection." - Simplicity: You prioritize modularity and clean design to reduce cognitive load in a complex logistics domain. - Transparency: You democratize data. You ensure insights are accessible across the organization and participate in constructive feedback loops. Equal Employment Opportunity Alvys is an equal opportunity employer and as such, we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable laws. We are dedicated to growing a diverse team of highly talented people. We’re dedicated to building a workplace where we give each other the strategies, support, and space we each need to thrive—believing in and bringing out the best of everyone. If you require any accommodations during the recruitment process, whether it be alternate forms of material, accessible meeting rooms, etc., please let us know and we will work with you to meet your needs. For information about Alvys's privacy practices, see our Privacy Policy.

• Own a product area end-to-end, including problem framing, implementation, rollout, and iteration. • Lead multi-person projects, write and review design docs, and make sound architectural decisions. • Build systems that are observable and reliable, participate in incident response, and drive post-incident improvements. • Partner closely with Product, Design, and operational stakeholders to ship high-leverage workflow improvements. • Mentor engineers through code reviews, pairing, and setting high standards for quality and product thinking. • Identify opportunities to simplify architecture, workflows, and UX to improve both customer experience and developer velocity.

• Lead technical initiatives, such as redesigning and implementing major platforms or infrastructures that impact various engineering teams. • Drive technical vision and architecture decisions across engineering teams, creating well-thought-out design documents that guide long-term work. • Research, create proofs of concept, and evangelize new technologies that enhance team capabilities and align with business objectives. • Own the technical architecture and delivery of large-scale, business-critical systems, ensuring they meet the highest standards for stability, performance, and scalability. • Think holistically about system architecture, reducing complexity to achieve more with less effort. • Mentor engineers across teams to accelerate their career growth and share knowledge through tech talks, design reviews, and code reviews. • Manage a smaller team of engineers (e.g., DevOps or Data teams) depending on organizational needs, balancing technical work with people leadership. • Challenge and improve team processes, ensuring projects are appropriately broken down, prioritized, and well understood. • Build effective relationships with product, design, and operations to translate business logic into engineering deliverables.

• Own the end-to-end product strategy and outcomes for Alvys’ financial suite, including Settlements, Invoicing, and Accounting. • Marry customer insights with technical possibilities to ensure AP/AR workflows are increasingly AI-native. • Work closely with Engineering, Design, Sales, and Implementation to drive high-velocity execution. • Rapidly build prototypes using tools like Bolt to accelerate the product development lifecycle. • Stay at the forefront of AI research and fintech trends to rethink how user roles evolve as AI automates routine tasks. • Ensure all financial products are robust and meet the demands of enterprise-scale customers.