Job Application

Role: GCP Architect
Job Type: Contract
Day Rate: £530- 550 per day (inside IR35)
Duration: will confirm shortly
Work Location: Sheffield/Manchester/Birmingham (northern counties) with ability to go to Sheffield weekly 2-3 times.
Position: 1

Please Note: Please look for additional experience in Fraud domain. Experience with a Fraud product called Feedzai would be a bonus and once you will apply for this role please revert me back your CV with below details because below details are mandatory from client side:

Please make sure below criteria's are met before sharing any profile.

Name:
Contact No:
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Total Years of Experience
Experience in LLM, Vertex AI, GCP, Data experience [Mandatory]
5+ years' experience architecting and designing cloud-based solutions
Years of Experience in Google cloud platform and its core services.
Years of Experience in machine learning concepts, model development, deployment, and governance.
Years of Experience in designing and building distributed systems, data pipelines and event driven architectures
Years of experience programming languages like Python and Java
Years of experience NoSQL and relational databases, data streaming platforms and distributed computing frameworks.
Years of experience Fraud domain with a Fraud product called Feedzai would be a bonus
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GCP Architect

We are seeking a visionary and technically adept to spearhead the definition and implementation of our next-generation technology infrastructure on Google cloud. The candidate will play a pivotal role in shaping our journey towards future-proof architecture by leveraging cutting edge technologies with a specific focus on integrating machine learning capabilities and paving the way for the adoption of large language models LLM's.

Responsibilities:

Collaborate with stakeholders across the organisation to identify opportunities for leveraging Google cloud ML&LLM's to solve complex business challenges.
Design and architect, scalable, secure and cost-effective cloud-based solutions using appropriate Google cloud services (eg Cloud Bigtable, cloud spanner, vertex AI & LLM platform etc.)
Drive adoption of best practises for machine learning including model development deployment and monitoring on Google cloud platform.
Champion the exploration and integration of large language models into existing and future solutions to enhance functionalities and capabilities.
Conduct research and stay abreast of emerging trends in cloud computing ML&LLM's translating theoretical concepts into practical applications for our organisation.
Development and maintain detailed technical documentation for future state architecture decisions and design implementation.
Partner with engineering teams to implement the designed architecture and ensure proper integration with existing systems.
Proactively identify and mitigate potential risks and challenges associated with new technologies and architectural transformations.
Effectively communicate complex technical concepts to diverse audiences fostering collaboration and buying across the organisation.

Skills and Experience:

Five plus years of experience in architecting and designing cloud-based solutions.
Strong understanding of Google cloud platform and its core services.
Proven experience with machine learning concepts, model development, deployment, and governance.
Familiarity with large language models and their potential applications in business context.
Expertise in designing and building distributed systems, data pipelines and event driven architectures.
Understanding in programming languages like Python and Java
Experience with NoSQL and relational databases, data streaming platforms and distributed computing frameworks.
Excellent communication collaboration and problem-solving skills.
Ability to work independently and as part of a cross functional team.
Passion for innovation and staying ahead of the curve in the tech landscape.

Bonus:

Experience with cloud security best practises and compliance requirements.
Familiarity with specific industry related Google cloud solutions and use cases.
Demonstrated experience with building and deploying LLMs within real world applications.