We are looking for a Senior II Software Engineer to join the CX Platform team, the foundational engineering team powering our entire Customer Experience group. This is a high-impact, hands-on role at the intersection of backend engineering, AI infrastructure, and customer-facing product.
You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
Why should you join us?
AI isn't a side project. It's a strategic priority, and the CX Platform team sits at the center of it. We own the AI infrastructure for the entire Product Offering group, which means your work has wide reach and real stakes.
You'll be working with modern agentic patterns, like AWS Bedrock and LangChain, building features that are genuinely novel and not just wrapping someone else's chatbot. If you want a role where backend depth, product instinct, and AI engineering all matter equally, this is it.
What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.
You'll work across the full platform stack (backend services, data pipelines, security, cost, and scale) with a meaningful and growing focus on AI infrastructure. We own the agentic platform for the entire Product Offering group: from building the LLM infrastructure and agentic workflows to ensuring they're reliable, observable, and safe in production.
Why should you join us?
AI isn't a side project. It's a strategic priority, and the CX Platform team sits at the center of it. We own the AI infrastructure for the entire Product Offering group, which means your work has wide reach and real stakes.
You'll be working with modern agentic patterns, like AWS Bedrock and LangChain, building features that are genuinely novel and not just wrapping someone else's chatbot. If you want a role where backend depth, product instinct, and AI engineering all matter equally, this is it.
What you'll be doing:
Own AI infrastructure for the Product Offering group. Design, build, and evolve the shared AI platform (agentic workflows, LLM integrations, observability, and guardrails) that CX product teams build on.
Ship agentic features end to end. Lead development of AI-driven capabilities using LangChain, LangFuse, and AWS Bedrock, from architecture through production deployment and monitoring.
Drive platform architecture. Set the technical direction for the CX backend (services, data pipelines, API patterns) with an eye for scalability, reliability, and developer experience.
Own core data foundations. Design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, and MySQL; keep pipelines fast, fresh, and reliable.
Mentor and elevate. Help engineers across the CX group grow in backend craft, AI engineering, and system design thinking.
Collaborate cross-functionally. Work with product, design, and customer-facing teams to turn ambiguous problems into well-scoped, high-quality solutions.
Requirements:
6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.
Itd be really cool if you also have:
6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.
Itd be really cool if you also have:
Experience with LangChain, LangGraph, LangFuse, or similar orchestration and observability tooling
Hands-on experience with AWS Bedrock or other LLM provider APIs
Experience designing or running AI evaluation frameworks (evals, LLM-as-judge, regression suites)
Familiarity with MCP (Model Context Protocol) or building tools for coding agents
Experience with React, Next.js, or micro-frontend architectures
Knowledge of Python for AI/data workflows.
This position is open to all candidates.
