Principal AI Engineering Architect
Robots and Pencils1 day ago
Remote, United StatesStaff+
Base Salary
$180k - $231k/yr
Responsibilities
- Define technical strategy and lead architecture across cloud, data, and AI/ML systems from research through production.
- Architect and ship production-grade multi-agent AI systems involving orchestration, tool use, memory, planning, and inter-agent communication.
- Design and operate AWS-native agentic workloads using Amazon Bedrock AgentCore and complementary AWS GenAI services.
- Design cloud-native, multi-cloud, and hybrid architectures, with AWS as the primary cloud and Azure, GCP, and Kubernetes as secondary platforms.
- Design data warehouses, data lakes, batch and streaming pipelines, ML platforms, model-serving systems, MLOps pipelines, and feature stores.
- Establish infrastructure-as-code, CI/CD, DevOps, security, governance, compliance, and observability standards across engagements.
- Lead cloud migrations and platform modernization while optimizing performance, scalability, cost, reliability, and safety.
- Partner with senior leadership and clients as the principal technical voice and translate complex AI tradeoffs for technical and non-technical stakeholders.
- Lead design reviews, maintain architecture standards and documentation, mentor engineers, and evaluate emerging agentic AI and AWS technologies.
Requirements
- At least 8 years of software engineering experience, including at least 5 years in technical leadership and 4 or more years focused on production AI/ML systems.
- Expert software engineering background in Python or a similar language, with strong scalable-system design skills.
- Deep hands-on expertise designing and shipping production multi-agent agentic AI systems.
- Deep AWS expertise, including AWS GenAI offerings and hands-on Amazon Bedrock AgentCore experience; Azure and GCP experience is a plus.
- Strong experience with microservices, serverless, containers, event-driven systems, infrastructure as code, and CI/CD.
- Strong data architecture experience across relational, NoSQL, and big-data systems, including data modeling, ETL/ELT, and orchestration.
- Mastery of AI frameworks and orchestration tools for agentic systems, plus production experience with LLMs, MLOps, model serving, and AI/ML frameworks.
- Experience building LLM and agentic application evaluation and observability capabilities.
- Deep understanding of AI safety, responsible AI, prompt-injection defenses, and PII handling.
- Extensive RAG experience covering chunking, embedding models, vector databases, and advanced retrieval.
- API design and integration experience at scale, with advanced cost-optimization expertise involving token economics, caching, model routing, and quantization.
- Solid understanding of cloud networking, security, identity and access management, governance, compliance, and observability.
- Track record of senior technical leadership, mentoring experienced engineers, stakeholder communication, and day-to-day expert use of Claude Code and Cursor.
- Multi-cloud architecture, responsible AI or AI ethics experience, and enterprise architecture certifications such as TOGAF or AWS, Azure, or GCP certifications are preferred.
Tech Stack
Amazon RedshiftApache AirflowApache KafkaApache SparkAWSAzuredbtDockerGitHub ActionsGoogle BigQueryGoogle Cloud PlatformKubernetesMLflowMongoDBPostgreSQLPythonPyTorchSnowflakeTensorFlowTerraform
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