Senior AI Engineer (US Remote

Company Overview

At Motorola Solutions, we believe that everything starts with our people. We're a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that's critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Noggin, a Motorola Solutions company, is a leader in integrated resilience management technology, offering a next-generation, cloud-based platform that combines 10 essential solutions into one unified system. Our award-winning platform seamlessly integrates operational and third-party risk management, operational resilience, business continuity, incident and crisis management, emergency management, and security and safety operations.

The Product Engineering area is responsible for designing, writing, testing and deploying the code for our software products at Noggin.

Join Motorola Solutions as a Senior AI Engineer and help shape the future of AI-powered products and services. Based in Sydney with hybrid flexibility, you'll work at the forefront of generative AI, building production-scale solutions using AWS Bedrock and cutting‑edge AI technologies.

As a senior member of our AI engineering team, you'll provide technical leadership, mentor engineers, and drive best practices in GenAI implementation. You'll work directly with Product Management and Software Engineering teams to transform AI use cases from concept to production, ensuring quality, safety, and scalability at every step.

Core AI Technologies:

• AWS Bedrock (Models, Agents, Knowledge Bases, Guardrails)
• Open Search & Vector Databases
• RAG (Retrieval-Augmented Generation) architectures
• Agentic frameworks (Lang Chain, Llama Index, or AWS Bedrock Agents)

Development Stack:

• Python (AI/ML development & data processing)
• NodeJS with Type Script (backend services)
• AWS ecosystem (S3, IAM, Cloud Watch, etc.)

AI Engineering Practices:

• Prompt engineering & optimization
• Model evaluation & testing frameworks
• AI observability & monitoring
• Responsible AI & safety practices

Required:

• Bachelor's degree in Computer Science, Software Engineering, or related field
• 5+ years in software development with 2+ years focused on production AI/GenAI systems
• Deep, hands‑on experience with AWS Bedrock, Knowledge Bases, and Open Search
• Proven track record designing and implementing RAG architectures at scale
• Proficiency in Python for AI/ML work and NodeJS/Type Script for backend development
• Experience with agentic frameworks and AWS Bedrock Guardrails
• Strong understanding of AI/ML concepts: models, agents, embeddings, vector databases
• Hands‑on experience with prompt engineering and model evaluation methodologies
• Knowledge of AI observability, monitoring, and responsible AI practices

Valued:

• Experience with multi‑modal AI capabilities
• Familiarity with model distillation and cost optimization techniques
• Background in AI safety, bias detection, or model explainability
• Contributions to open‑source AI projects or research publications

• Technical Leadership:
  Apply your expertise in GenAI, AWS Bedrock, and related technologies to drive architectural decisions and coach team members
• End‑to‑End AI Development:
  Design, build, and refine AI use cases including guardrails, evaluation frameworks, and quality assurance
• Collaboration:
  
  Partner with Product Management and Software Engineering teams to realize AI features from concept to production
• Advisory Role:
  Provide technical guidance to management, team leads, and customers on AI implementation strategies
• Community Engagement:
  Actively contribute to technology chapter meetings and knowledge sharing

• Building production‑scale GenAI applications using AWS Bedrock and foundation models
• Implementing RAG systems with Knowledge Bases and vector search
• Designing AI agents that can reason, plan, and execute complex workflows
• Establishing prompt engineering best practices and…