Live opening · Posted 17 days ago
The key details from the original listing.
Live timing from JobBeeper.
Description supplied by the original job listing.
JOB SUMMARY
We are looking for a highly experienced Forward-Deployed AI Engineer who can work closely with customers, understand real-world business and technical requirements, and translate them into production-ready AI/ML solutions. This role combines AI engineering, software development, solution implementation, customer interaction, troubleshooting, and deployment.
KEY RESPONSIBILITIES
Work directly with customers and technical stakeholders to understand business and technical requirements.
Translate requirements into scalable AI/ML and software solutions.
Design, develop, integrate, and deploy AI-powered applications.
Work closely with platform, DevOps, and deployment teams to take solutions into production.
Integrate AI/ML models with APIs, applications, databases, and enterprise systems.
Build proof-of-concepts and rapidly convert them into production-ready implementations.
Troubleshoot application, AI/ML, integration, and deployment issues.
Participate in technical discovery, solution design, demonstrations, and customer discussions.
Develop automation and reusable components to accelerate future deployments.
Create technical documentation, deployment guides, and operational runbooks.
Support onboarding, knowledge transfer, and technical training.
Be willing to travel or work on-site when deployment requirements demand it.
SKILLS & QUALIFICATIONS
REQUIRED SKILLS
GOOD TO HAVE
• 8+ years in software engineering, AI/ML engineering, or a related technical field.
• Generative AI, LLMs, RAG, vector databases, or AI agents.
• Strong Python development experience.
• MLOps experience.
• Experience building and deploying AI/ML applications.
• Kubernetes/Helm-based deployments.
• Strong understanding of REST APIs, microservices, and integrations.
• Enterprise customer implementation experience.
• Experience with databases and data-processing pipelines.
• Solution engineering or technical consulting.
• Experience with AWS, Azure, or GCP.
• SaaS/product deployment experience.
• Docker and containerized application experience.
• Customer-site deployment experience.
• Working knowledge of Kubernetes.
• Strong Git, testing, CI/CD, and debugging fundamentals.
• Excellent customer-facing communication skills.
• Ability to turn ambiguous requirements into technical solutions.
Work arrangement
No
Recently tracked roles with full details and direct application links.