Senior Software Engineer, Agentic Platform
Listed on 2026-02-16
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Software Development
AI Engineer, Software Engineer, Cloud Engineer - Software, Machine Learning/ ML Engineer
THE POSITION
We're looking for a talented senior Software Engineer to join our Agentic Platform team—the group responsible for building the company-wide infrastructure that enables every engineering team to safely build AI-powered features. This is a rare opportunity to shape foundational AI/LLM platform capabilities from the ground up at a company that's deploying real-world AI agents today.
The Agentic Platform provides shared primitives, hosted agent execution, and operational tooling so any team can build AI-powered workflows—from simple summarization to complex multi-turn conversational agents. Our vision: enable any engineer to build production-ready AI features without becoming an AI expert.
The platform handles the hard infrastructure problems—provider abstraction, safety guardrails, observability, prompt lifecycle management, and evaluation systems—so product teams can focus on their domain logic. You'll be working on:
Agentic Platform SDK:
Type Script SDK with core primitives (Completion, Agent, Tool, Guardrail, Prompt Pack, Eval, Context)Agentic Platform Service:
Agent-as-a-Service for long-running async tasksPrompt Management:
Externalized, versioned prompt storage with CI/CD IntegrationOur production AI-powered voice and chat application—the proving ground for platform patterns
Reporting to the Director of Engineering, you'll partner closely with the Principal Engineer leading platform architecture while collaborating with product teams across the company who will consume your platform. This role is ideal for someone who thrives in technically deep problems, wants to build infrastructure that multiplies the impact of other engineers, and is excited about the rapidly evolving LLM landscape.
WHOYOU ARE
You're a platform engineer at heart—someone who understands that the best infrastructure is invisible to its users while handling enormous complexity under the hood. You have a track record of designing systems that other engineers love to use, and you know how to balance powerful abstractions with practical simplicity.
You understand that LLM systems present unique challenges: non-deterministic outputs, rapidly evolving provider SDKs, safety requirements, and the need for systematic quality measurement. You're excited to tackle "churn containment"—building stable APIs that absorb the chaos of monthly model releases and quarterly SDK updates.
The ideal candidate is a hands‑on, outcome‑oriented engineer with extensive experience building platform infrastructure, developer tools, or distributed systems. You demonstrate a strong partnership with internal customers (other engineering teams), ensuring alignment between platform capabilities and their needs.
WHAT YOU WILL DODesign and build core platform primitives including provider abstraction layers (OpenAI, Anthropic, Google), structured output validation, streaming infrastructure, and token management systems
Own safety and compliance infrastructure including composable guardrail systems, PII detection/redaction, audit logging, and privacy‑first observability that never leaks sensitive data to third parties
Build evaluation infrastructure that enables systematic quality measurement for non-deterministic LLM outputs—datasets, scorers (exact match, LLM-as-judge, schema validation), CI/CD integration, and regression detection
Lead churn containment strategy—design provider adapters and SDK architecture that absorbs rapidly‑changing LLM provider SDKs without breaking consuming applications
Architect prompt lifecycle management systems including version control, Langfuse integration, Git Hub‑based review workflows, and deployment pipelines
Design Agent‑as‑a‑Service infrastructure for long‑running async tasks using AWS Event Bridge, Dynamo
DB, and PostgreSQLCollaborate with consuming teams to understand their needs, onboard them to the platform, and provide technical support
Influence architecture, technology selections, and engineering standards across the broader organization
Create reference implementations and technical documentation that enables other engineers to successfully adopt the platform
Champion quality engineering practices including…
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