AI Engineering Manager/solutions Architect – Sfl Scientific

AI Engineering Manager/Solutions Architect role at Deloitte's SFL Scientific, focused on designing, developing, and deploying AI applications for clients across various sectors. The role involves leading client engagements, defining data strategy, architecting scalable AI platforms and cloud solutions, and adopting best engineering practices. It requires expertise in modern data architecture, data science engineering, and supporting AI/GenAI use cases, with a platform-agnostic approach.

What you'd actually do

  1. Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  2. Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  3. Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  4. Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  5. Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem

Skills

Required

  • AI Engineering
  • Solutions Architecture
  • Machine Learning
  • Automation
  • Data Architecture
  • Data Science Engineering
  • Data Transformation
  • Cloud Computing
  • On-prem technologies
  • Scalable architecture design
  • High-performance data architecture
  • Data pipelines
  • Database schemas (Graph, SQL, NoSQL)
  • Algorithm scalability
  • Deployment
  • Agile methodologies
  • DevOps
  • LLM/MLOps
  • Data Engineering
  • HPC

Nice to have

  • Leadership
  • Consulting
  • Mentoring
  • Thought leadership

What the JD emphasized

  • design, development, and deployment of novel AI applications
  • design and deliver architecture for complex AI and R&D type problems
  • AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources
  • leading application deployment
  • develop robust AI platforms and cloud solutions
  • design and lead development on scalable, high-performance data architecture solutions
  • AI/GenAI use cases
  • AI/GenAI infrastructure

Other signals

  • design, development, and deployment of novel AI applications
  • design and deliver architecture for complex AI and R&D type problems
  • develop robust AI platforms and cloud solutions
  • design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases