Senior Engineer

Overview: Own design and delivery of core AI infrastructure capabilities used across all AI products.Build and operate reusable AI infrastructure services that enable teams to develop, deploy, and scale Agentic AI and Generative AI applications securely and reliably. This role focuses on building foundational AI platform capabilities including LLMOps, observability, governance, guardrails, retrieval systems, orchestration frameworks, and runtime infrastructure for autonomous AI agents. Key Responsibilities: Build AI Infrastructure to support a team of Agentic and GenAI app developers.

This including building systems for Guardrails, Observability, Governance, LLMOps, agent to agent orchestration, Traceability and other such infra elements that are unique to AI systems. This includes the following Build and maintain the foundational infrastructure for agentic AI systems including orchestration layers, tool registries, and execution environments that support multi-step, autonomous agent workflows Design reliable and observable agent runtimes implement tracing, logging, and replay tooling across long-running agent sessions, with support for interrupt/resume, sandboxing, and failure recovery (e.g. LangSmith, Arize, custom OpenTelemetry pipelines) Own memory and context infrastructure architect short- and long-term memory stores, manage context window strategies, and build retrieval systems that give agents reliable, low-latency access to the right information at the right time Develop and operate tool/API integration layers build secure, rate-limit-aware, and schema-validated connectors that agents use to interact with external systems, ensuring safe and auditable tool execution Define guardrails and safety infrastructure for autonomous agents* implement policy enforcement, output validation, human-in-the-loop checkpoints, and permission scoping to ensure agents operate within defined boundaries in production Qualifications: Experience 810 years backend/platform engineering At least 34 years working on ML/AI platforms (traditional ML, Gen AI, and agentic) Nice to Have Experience with model fine-tuning or LoRA Exposure to GPU workloads or inference optimization Competencies: Platform thinking Reliability engineering Technical ownership