Principal AI Engineering Architect

Partner with senior leadership and clients as the principal technical voice on strategy and direction Translate complex AI tradeoffs, risks, and opportunities into clear narratives that drive decision-making across technical and non-technical stakeholders Lead design reviews and technical discussions, raising the bar for engineering rigor and constructive challenge across the team Engage closely with engineering, data, AI, and product teams to align architecture with broader business priorities Develop and maintain architecture documentation, standards, and guidelines

Define and champion architectural standards and best practices across the engagements you support, bringing depth on tradeoffs, long-term implications, and responsible AI practices Mentor and grow engineers at all levels, multiplying impact through coaching, code reviews, and pairing on hard problems Own the most difficult architectural, integration, and agentic-system challenges, serving as the senior technical decision-maker and driving them through to production with care for reliability, cost, and safety Evaluate emerging technologies — especially in the agentic AI and AWS ecosystems — and recommend tools, frameworks, and patterns that improve architecture over time

8+ years of software engineering experience, with at least 5 years in technical leadership roles and 4+ years focused on AI/ML systems in productionExpert software engineering background (Python or similar) with strong design sensibilities for scalable, maintainable systems Deep, hands-on expertise designing and shipping production multi-agent agentic AI systems, including agent orchestration, planning, tool use, and multi-agent coordination patterns Deep expertise with AWS, including in-depth knowledge of AWS GenAI offerings and hands-on experience with Amazon Bedrock AgentCore; broader multi-cloud experience (Azure, GCP) is a plus Strong background in microservices, serverless, containers, and event-driven systems (e.g., Kubernetes, Docker, Lambda, EventBridge) Proficiency with infrastructure as code and CI/CD (e.g., Terraform, CloudFormation, Pulumi, GitHub Actions) Strong data architecture expertise across relational, NoSQL, and big data systems (e.g., PostgreSQL, MongoDB, Snowflake, BigQuery, Spark, Kafka) Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration (e.g., Airflow, Prefect, dbt) Mastery of AI frameworks and orchestration tools for building agentic systems (e.g., LangChain, LangGraph, AgentCore, CrewAI, AutoGen, or equivalents) Strong experience designing AI/ML systems for production, including LLMs, MLOps, and model serving (e.g., SageMaker, Bedrock, Vertex AI, MLflow, Hugging Face, PyTorch, TensorFlow) Strong experience with evaluation frameworks and observability tools for LLM and agentic apps, including building these capabilities where they don't yet exist Deep understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling Extensive experience building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques API design experience, including architecting and integrating with internal and third-party services at scale Advanced cost optimization expertise: token economics, caching strategies, model routing, quantization Solid understanding of networking, security, identity, and access management in cloud environments Experience with governance, compliance, and observability frameworks Track record of senior technical leadership and mentoring experienced engineers Strong stakeholder communication skills, with the ability to translate technical depth across audiences Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude Code and Cursor Multi-cloud architecture experience, AI ethics or responsible AI experience, or enterprise architecture certifications (e.g., TOGAF, AWS/Azure/GCP) is a plus

Our salary range is $180,375 – $230,625 USD