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Principal AI Engineering Architect

19 minutes ago
United States
Full-time
Lead
Infrastructure Engineer
DevOps and Infrastructure
Apache Airflow Apache Spark AWS Azure CloudFormation dbt Docker GCP GitHub Actions HIPAA Hugging Face Kafka Kubernetes LLM Machine Learning Microservices MLflow MongoDB PostgreSQL Prefect Pulumi Python PyTorch SageMaker Serverless Snowflake TensorFlow Terraform Vertex AI
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Robots & Pencils

Robots & Pencils

Robots & Pencils is a digital innovation firm that assists organizations in leveraging mobile, web, and AI technologies to modernize their operations and create efficient, user-centered solutions that enhance productivity and decision-making.

IT Services
51-250
Founded 2009
View All Jobs 16

Description

  • Define technical strategy and lead architecture across cloud, data, and AI/ML systems from research through production.
  • Architect and deliver production-grade multi-agent agentic AI systems, including orchestration, tool use, memory, and inter-agent communication.
  • Design and build secure production workloads using Amazon Bedrock AgentCore and other AWS GenAI services.
  • Architect cloud-native solutions with AWS as the primary platform and multi-cloud or hybrid approaches where needed.
  • Design data architectures for warehouses, data lakes, and batch or streaming pipelines.
  • Design and evolve AI/ML systems, including model serving, MLOps pipelines, feature stores, and LLM-based applications.
  • Build scalable ML platforms, pipelines, and infrastructure that support repeatable model development and deployment.
  • Define infrastructure-as-code, CI/CD, and DevOps standards across engagements.
  • Optimize deployed systems for performance, scalability, cost, reliability, security, governance, and compliance.
  • Partner with leadership, clients, engineering, data, AI, and product teams as the principal technical voice; mentor engineers and lead design reviews.

Requirements

  • 8+ years of software engineering experience.
  • At least 5 years in technical leadership roles.
  • 4+ years focused on AI/ML systems in production.
  • Expert software engineering background in Python or a similar language.
  • Deep, hands-on experience designing and shipping production multi-agent agentic AI systems.
  • Deep expertise with AWS, including AWS GenAI offerings and Amazon Bedrock AgentCore.
  • Broad multi-cloud experience with Azure or GCP is a plus.
  • Strong background in microservices, serverless, containers, and event-driven systems.
  • Proficiency with infrastructure as code and CI/CD tools such as Terraform, CloudFormation, Pulumi, and GitHub Actions.
  • Strong data architecture experience across relational, NoSQL, and big data systems.
  • Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration tools such as Airflow, Prefect, and dbt.
  • Mastery of AI frameworks and orchestration tools such as LangChain, LangGraph, AgentCore, CrewAI, and AutoGen.
  • Strong experience designing production AI/ML systems, including LLMs, MLOps, and model serving.
  • Experience with evaluation frameworks and observability tools for LLM and agentic applications.
  • Deep understanding of AI safety, responsible AI, prompt injection defenses, and PII handling.
  • Extensive experience building RAG pipelines.
  • API design and systems integration experience at scale.
  • Advanced cost optimization expertise, including token economics, caching, model routing, and 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.
  • Daily expert use 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 such as TOGAF or AWS/Azure/GCP are a plus.

Benefits

  • Salary range of $180,375–$230,625 USD.
  • Opportunity to work on production-ready AI delivered in 30 to 45 days.
  • High ownership and influence on technical direction and long-term system success.
  • Work on complex, high-impact enterprise AI engagements.
  • Mentorship and growth opportunities through coaching and pairing with senior engineers.

Interested in this position?

Apply directly on the company website

Apply Now

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