Senior Lead Software and Data Engineer - Agentic Commerce

About the job

Responsibilities

• Set technical direction and reference architecture for B2B agentic commerce, including multi-agent topology, agent-to-agent communication, tool integration, and LLM reasoning boundaries.
• Design information barriers and authorization for agents acting on behalf of different counterparties, ensuring isolated execution for potentially adversarial tenants.
• Define the MLOps architecture for models used as agent tools, covering training, environment promotion, model registry, serving, monitoring, and retraining.
• Establish engineering standards for agent quality and safety, including evaluation frameworks, guardrails, observability, and model risk approval requirements.
• Develop and troubleshoot creative software solutions, thinking beyond conventional approaches.
• Write secure, high-quality production code for critical paths and review/debug code written by others.
• Partner with platform teams, product, risk, and client-facing teams for reusable capabilities and external agent integration.
• Drive team adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Apply knowledge of the Software Development Life Cycle toolchain, including AI-assisted development, to enhance automation value.
• Identify opportunities to eliminate or automate remediation of recurring issues for improved operational stability.
• Lead evaluation sessions with external vendors and internal teams to assess architectural designs and technical applicability.
• Mentor engineers and raise the technical bar through design reviews and architecture decisions.

Requirements

• Formal training or certification in software engineering concepts and advanced applied experience.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in at least one programming language, with strong Python and/or Java experience required.
• Deep understanding of concurrency and distributed computation, with proven experience in multithreaded/multi-process systems, worker/task-queue architectures, and observable distributed workloads.
• Proven experience architecting and shipping production LLM agents or multi-agent systems, including tool use, memory, evaluation, and guardrails.
• Proven experience designing end-to-end ML platforms or MLOps pipelines from training through serving and monitoring.
• Experience designing secure distributed systems, including identity, authorization, and service-to-service trust.
• Demonstrated experience leading effective use of approved AI-assisted software development tools and setting team expectations for validating AI outputs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling, and adherence to resiliency/security expectations.
• Proficiency in all aspects of the Software Development Life Cycle.
• Advanced understanding of agile methodologies like CI/CD, Application Resiliency, and Security.
• In-depth knowledge of the financial services industry and their IT systems.
• Practical cloud-native experience.
• Deep proficiency with Kubernetes and Amazon EKS, micro-VM isolation, and sidecar architectures, with proven experience in defense-in-depth across the stack.