AI Agentic Solutions Engineer

One of Confiz’s largest retail clients is seeking an experienced AI Agentic Solutions Engineer to serve as a lead individual contributor responsible for driving technical excellence and the overall quality of the team’s work. This role requires the ability to independently tackle complex technical design and problem-solving challenges while maintaining a strong product mindset.

The ideal candidate will design and deliver scalable systems spanning multiple weeks or months of development, establish a strong point of view on effective agent user experiences, and make thoughtful technical decisions that balance short- and long-term business objectives. This individual will also take ownership of team-level costs, performance metrics, and technical outcomes.

In addition, the AI Agentic Solutions Engineer will champion emerging technologies and engineering practices, mentor junior engineers, and serve as a key technical voice in cross-functional discussions with product, business, infrastructure, and security stakeholders.

This is a hybrid role based in Seattle, WA. Onsite presence of 4 days per week is expected with an 8:00 am - 5:00 pm work schedule.

Responsibilities

• Partner with business and technology stakeholders to define the “art of the possible” with agents — translating ambiguous problems into agentic solutions with clear success criteria and measurable outcomes.
• Design and build core agentic solutions end-to-end across orchestration, tool-use pipelines, and integration with enterprise systems.
• Own end-to-end solution design for agentic solutions spanning multiple engineers’ work, with full upstream/downstream integration consideration.
• Apply context engineering to determine what an agent sees, when, and why — balancing token economics, latency, and decision quality across RAG patterns, structured retrieval, and dynamic prompt assembly.
• Develop and own evaluations and guardrails that demonstrate solutions are safe, reliable, and accurate — offline benchmarks, online production telemetry, and failure-mode analysis.
• Architect memory and state management approaches that let agents reason across sessions, users, and workflows — short-term context, long-term memory, and durable conversation state.
• Apply AI fluency to integrate LLM APIs, embedding models, vector stores, and agentic frameworks into production services; evaluate and adopt emerging techniques as appropriate.
• Make and clearly articulate technical trade-offs between short-term delivery needs and long-term scalability, factoring in design, framework choice, model selection, and infrastructure costs.
• Design systems accounting for current and upcoming product cycles, team-level cost responsibility, and alignment with cross-functional roadmaps.
• Lead design and code reviews across the team; provide actionable feedback and maintain a high bar for quality, testability, and extensibility.
• Design key metrics, evaluations, and observability patterns for agentic solutions; drive accountability for performance, cost, accuracy, and security of feature work.
• Work with business, infrastructure, and security teams to deliver enhancements, reliability improvements, and bug fixes for production AI systems.
• Surface potential design or delivery conflicts in the current or upcoming product cycle and make clear recommendations on the best path forward.
• Mentor and support junior engineers across a wide spectrum of technical activities; participate in hiring interviews with clear, specific feedback.
• Ensure own work and team members’ work follows Nordstrom’s engineering and security standards; contribute to those standards

Qualifications

• 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.
• Experience designing, building, and operating AI agents or agentic workflows in production, including tool-use, orchestration, and integration with downstream systems.
• Strong understanding of how to assemble, prune, and structure context for agents to maximize decision quality within token, latency, and cost constraints.
• Experience designing evaluation frameworks and safety guardrails for LLM-based systems, including offline benchmarks, online telemetry, and responsible deployment practices.
• Familiarity with short-term and long-term memory patterns for agents, vector stores, conversation state, and durable workflow state.
• Hands-on experience with agentic frameworks such as Claude Agent SDK, LangGraph, AutoGen, CrewAI, Semantic Kernel, or OpenAI Assistants API.
• Familiarity with multi-agent orchestration patterns: task decomposition, tool-use pipelines, and human-in-the-loop workflows.
• A product-minded approach to engineering: strong instincts for user impact, comfortable pushing back on requirements when the right solution isn’t the one initially asked for, and able to translate business intent into agentic capabilities.
• Proficiency in Python; strong grasp of multiple tech stacks and cloud-native development on AWS and/or GCP.
• 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

• 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).
• Strong emphasis on building observability into systems — real-time alerting, dashboards, metrics, and performance accountability.
• 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 services.
• Contributions to open-source AI projects; curiosity and engagement with the broader AI/ML engineering community

We have a global team of amazing individuals working on highly innovative enterprise projects & products. Our customer base includes Fortune 100 retail and CPG companies, leading store chains, fast growth fintech, and multiple Silicon Valley startups. What makes Confiz stand out is our focus on processes and culture. Confiz is ISO 9001:2015 (QMS), ISO 27001:2022 (ISMS), ISO 20000-1:2018 (ITSM) and ISO 14001:2015 (EMS) Certified. We have a vibrant culture of learning via collaboration and making workplace fun.

People who work with us work with cutting-edge technologies while contributing success to the company as well as to themselves.

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