Principal Engineer

Iterable Iterable · Enterprise · San Francisco, CA · Remote · Engineering

Principal Engineer role focused on driving technical strategy and architectural coherence for an AI-powered customer engagement platform. Responsibilities include establishing technical standards, mentoring engineers, and overseeing design documents. Requires experience with Multi-Agent Frameworks, multiple LLMs, and orchestration software like LangGraph.

What you'd actually do

  1. Serve as the technical authority for multiple core product areas, ensuring all architectural decisions directly support the business objectives for those areas.
  2. Establish and maintain organization-wide technical standards, architectural patterns, and coding best practices to ensure consistency, security, performance, and maintainability across all teams.
  3. Directly mentor, guide, and lead the technical direction of the Tech Leads and senior engineers within the domains, fostering a high-performance engineering culture.
  4. Oversee and approve key design documents and high-level architectural proposals, ensuring they adhere to organizational standards and the own building and maintaining a long-term architectural roadmap.
  5. Define and communicate the overall architectural vision and strategy to engineering teams, helping them understand how their individual contributions connect to the broader product and business goals.

Skills

Required

  • 10+ years of software engineering experience
  • 5+ years as a hands on architect
  • System Design
  • Microservices
  • Event-Driven Architecture
  • cloud environment (AWS/GCP/Azure)
  • Scala
  • Java
  • Play
  • Kafka
  • Flink
  • Pulsar
  • S3
  • Multi-Agent Frameworks
  • Multi-Agent Systems
  • LLMs (OpenAI, Anthropic, Cohere, etc.)
  • LangGraph
  • Data engineering
  • Data pipeline technologies
  • SQL
  • NoSQL databases
  • caching strategies
  • data consistency models
  • Elasticsearch
  • Postgres
  • Redis
  • CockroachDB
  • CI/CD pipelines
  • observability (logging/monitoring/tracing)
  • DevOps practices
  • consumer-scale systems
  • enterprise software companies
  • Influence without Authority
  • Business Acumen
  • Mentorship

What the JD emphasized

  • architecting and delivering complex, high-scale, distributed systems
  • Deep expertise in our core technology stack: Scala (Java in lieu), Play, Kafka, Flink, Pulsar, S3
  • Experience building or deploying Multi-Agent Frameworks or Multi-Agent Systems.
  • Proven experience working with multiple LLMs (e.g., OpenAI, Anthropic, Cohere, etc.) and understanding their strengths and limitations.
  • Expertise in orchestration software like LangGraph or similar frameworks used for building and managing agent workflows.

Other signals

  • AI-powered customer engagement platform
  • Multi-Agent Frameworks or Multi-Agent Systems
  • working with multiple LLMs