Engineer Senior 2, AI Agentic Platform

Job Description

Client is investing in AI as a core driver of retail innovation, and the AI Agentic Platform team is building the shared foundation that makes it possible. Our platform enables AI agents to autonomously reason, use tools, coordinate across systems, and take action on behalf of customers and business teams powering experiences across commerce, personalization, inventory, and customer service.

Skills

• 6+ years of professional software engineering experience, with a strong track record of designing and delivering complex, scalable distributed systems.
• AI Fluency Required: Hands-on experience working with LLMs, foundation model APIs (OpenAI, Anthropic, Google, etc.), prompt engineering, retrieval-augmented generation (RAG) architectures, and embedding-based search in production environments.
• Platform engineering in AI teams: You have contributed to or built shared AI infrastructure or developer platforms within an AI-focused product organization, enabling other teams to build reliable AI-powered features on top of your foundation.
• Proficiency in Python and/or Java; strong grasp of multiple tech stacks and cloud-native development on AWS and/or GCP.
• Experience with RESTful services, event-driven architectures, and backend databases (SQL, NoSQL, or cloud-native datastores).
• Familiarity with containerization technologies (Kubernetes, Docker) and modern CI/CD practices and tools (e.g., GitLab).
• Demonstrated ability to design systems spanning multiple weeks or months of work, incorporating a full team's worth of engineers, and balancing short and long-term trade-offs.
• Strong emphasis on building observability into systems, real-time alerting, dashboards, metrics, and performance accountability.
• Experience working with cross-functional teams including product, business, infrastructure, and security stakeholders.
• Strong verbal and written communication skills; ability to articulate complex technical decisions to both technical and non-technical audiences.
• Agile development experience (Scrum, Kanban, Lean, or similar) with a continuous improvement and quality mindset.
• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.

Nice to Have

• Hands-on experience building AI Agentic systems, designing or deploying autonomous agents using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or OpenAI Assistants API.
• Familiarity with multi-agent orchestration patterns: task decomposition, tool-use pipelines, short-term and long-term agent memory, and human-in-the-loop workflows.
• Experience with agent evaluation frameworks, safety guardrails, and responsible deployment of AI agents in production environments.
• Background in retail, e-commerce, or supply chain domains, understanding of how AI agents can drive value in inventory, fulfillment, personalization, or customer service.
• Experience with big data technologies (Spark, BigQuery, Redshift) and integrating ML models into production platform services.
• Contributions to open-source AI or platform projects; curiosity and engagement with the broader AI/ML engineering community.

Engineering Competencies

• Architecture & Design: Designs systems where implementation spans multiple weeks or months. Makes technical decisions and influences priorities and trade-offs for short and long-term objectives. Champions new techniques across the organization.
• Engineering Practices: Strong understanding of business and how strategies and tactics work. Leads work processes and design reviews across the team. Directs best practices for incident resolution and cross-functional troubleshooting. Identifies potential gaps and solutions to problems before they exist.
• Quality & Instrumentation: Leads the team in keeping code and systems well-designed and well-documented. Takes the lead on key system and code reviews. Owns team-level metrics and events. Drives accountability for team-level application performance. Acts as a subject matter expert in one or more technical areas.
• Leadership: Mentors and coaches junior engineers. Participates in interviews for individual contributor roles with clear, specific feedback. Contributes beyond the scope of their own team.