Senior Ecommerce Backend Engineer: AI - Native

Edmund Optics•,

29d•$120,000 - $135,000•Onsite

About The Position

Edmund Optics is seeking a Senior Ecommerce Backend Engineer: AI-Native to build, integrate, and expand the backend services that power the company's evolving modular ecommerce platform. This is a hands-on software engineering role focused on connecting core ecommerce capabilities including personalization, semantic and LLM-driven search and discovery, Digital Asset Management (DAM), Product Information Management (PIM), and internal SAP/HANA systems. The role will design and develop APIs, services, data flows, and integrations that allow these platforms to work together reliably at scale. A defining requirement for this position is an AI-native development mindset: the successful candidate will use AI coding agents as a normal part of the software development lifecycle to generate, refactor, test, debug, document, and improve code while applying strong engineering judgment, security practices, and human review. The ideal candidate combines strong backend engineering fundamentals, systems integration experience, curiosity, and the ability to move quickly in a modern AI-assisted development environment.

Requirements

Strong hands-on backend software engineering experience building production web applications, services, APIs, and integrations.
Demonstrated ability to use AI coding agents and AI-assisted development tools to write, refactor, test, debug, and document code as part of a professional software development workflow.
Strong engineering judgment and the ability to review, validate, and improve AI-generated code for correctness, security, performance, maintainability, and architectural fit.
Experience designing and consuming RESTful APIs, service integrations, data interfaces, and modern backend application patterns.
Experience integrating multiple enterprise or SaaS platforms within a production web or ecommerce environment.
Strong understanding of databases, data modeling, SQL, system-to-system data flows, error handling, and integration reliability.
Experience with source control, automated testing, code review, CI/CD practices, logging, monitoring, and production troubleshooting.
Ability to work effectively with frontend developers, architects, product and ecommerce teams, data teams, enterprise application owners, and external implementation partners.
Strong problem-solving skills, curiosity, and comfort working in an evolving environment where architecture and tools will continue to change.
Ability to communicate technical concepts, tradeoffs, risks, and dependencies clearly to both technical and non-technical stakeholders.
Ability to work onsite in Barrington, New Jersey.
Comply with federal, state, and company policies, procedures, and regulations.
US Citizenship or permanent residence required.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related technical field; equivalent relevant experience will be considered.
7+ years of professional software development experience, including substantial hands-on backend, API, or systems integration work.
Demonstrated recent experience using AI-assisted or agentic coding workflows in real software development, not solely experimentation or prompt-based prototyping.

Nice To Haves

Experience with B2B ecommerce, technical products, manufacturing, or another complex product and transaction environment.
Experience integrating ecommerce platforms with PIM, DAM, personalization, semantic search, LLM/RAG capabilities, ERP, analytics, or related enterprise systems.
Experience working with SAP and/or SAP HANA data and integration patterns.
Experience with modern cloud services, message/event-based integration patterns, caching, search platforms, or distributed service architectures.

Responsibilities

Design, build, maintain, and extend backend services, APIs, and integration layers that support Edmund Optics' modular ecommerce architecture and customer-facing web experiences.
Use AI coding agents and AI-assisted development workflows as a core part of day-to-day engineering to generate, refactor, test, debug, document, and accelerate production code. Validate AI-generated output for correctness, security, maintainability, and performance rather than treating generated code as automatically production-ready.
Integrate key ecommerce capabilities including personalization platforms, semantic/LLM search and discovery, DAM, PIM, analytics and data services, and other modular components as the ecommerce ecosystem evolves.
Build and maintain reliable integrations between the ecommerce platform and internal enterprise systems, including SAP/HANA, product, pricing, inventory, customer, order, and other business data required to support ecommerce experiences and transactions.
Develop scalable, secure, well-documented APIs and services that allow internal applications, third-party platforms, and customer-facing experiences to exchange data efficiently and consistently.
Partner with ecommerce, search, data, and AI teams to integrate LLM-enabled and semantic capabilities into the site, including retrieval, product discovery, conversational experiences, and supporting data pipelines or service layers.
Build automated testing and validation into development workflows. Use AI-assisted debugging where appropriate while maintaining strong standards for code review, observability, performance, regression prevention, and production reliability.
Develop services and components with clear boundaries, reusable interfaces, and maintainable integration patterns that support continued movement toward a more modular and composable ecommerce architecture.
Work directly with technology vendors, implementation partners, and internal teams to understand technical requirements, review integration approaches, troubleshoot issues, and translate platform capabilities into production solutions.
Stay current with AI-assisted software development, agentic coding workflows, backend architecture, integration patterns, and emerging ecommerce technologies. Evaluate new approaches pragmatically and adopt those that measurably improve engineering speed, quality, or maintainability.