Participate in developing Generative AI Platform Capabilities
Responsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)
Participate in day-to-day standups for platform capability build
Research industry best practices, evaluate new technologies, develop standards and engineering best practices and recommend innovative solutions that support automation and improve platform resiliency and fault tolerance of critical applications
Execute on roadmaps that align with technology and business strategy. Perform hardware and capacity planning, analysis and forecasts for your portfolio of applications with focus on highest availability, scalability, performance, and timely delivery
Act as an expert resource for other technical teams within DTI
Minimum Requirements:
5+ years of Python experience
5+ years of big data experience needed (Big Query, Hadoop)
5+ years with Linux O/S capabilities
3 years of experience in AIML area (MLOps)
3+ years of Pyspark experience
3+ years with VMWare Virtualization technologies
Working knowledge of Auto ML technologies such as H2O Driverless AI, DataRobot, VertexAI, Elastic and Vector DB
Excellent verbal, written, and interpersonal communication skills. Ability to articulate technical solutions to both technical and business audiences
Recent and demonstrated ability to influence management on technical or business solutions
Working knowledge of design and build grid computing with CPU and GPU supporting AIML and NLP
Working knowledge of high-performance storage technologies along with Object Storage
Knowledge and understanding of network infrastructure to support high throughput and low latency grid computing
Preferred Skills:
1+year of experience in LLM , Generative AI (developing capabilities or dev/ops)
Experience in developing of API on GCP/Azure/API Gateways
1+year of experience in Elastic Search, Vector Database, Model Development would be added benefit.
Experience with data processing technology (AbInitio, Informatica, IBM DataStage)
Experience with large data technology (Hadoop, Teradata, Elasticsearch, etc.)
Understanding of Agile practices and ability to work with Agile teams to define and track user stories
Experience with implementing complex F5 or other Load Balancer Technologies
Working knowledge of building high resiliency grid/cloud computing infrastructure supporting AIML and NLP workloads
Knowledge and understanding of Cloud computing, PaaS design principles and micro services and containers
Working knowledge/experience with Azure and/or GCP, as well as some experience building complex infrastructure programmatically with IaC tools (Terraform/Ansible etc.)
Working knowledge/experience with on-premise and Public Cloud technologies, such as Cloud Foundry, Kubernetes, Docker
Experience in leading / facilitating analysis of current systems and problem identification and resolution
Ability to lead / facilitate technically complex discussions and working sessions in person or via teleconference