Job Description
As an AI Engineer, your role will be to develop the AI engineering strategy, supporting our Banking clients to design, implement, and operate scalable AI solutions across their businesses, playing a critical role in designing, implementing, and integrating AI solutions with existing enterprise systems.
Key Responsibilities
Translating the vision of senior client stakeholders and senior Deloitte AI engineers into a delivery and implementation roadmap, ensuring alignment with strategic goals and digital transformation efforts.
Collaborating with Enterprise, Application, Data, and DevOps Architects, Data Scientists, MLOps and GenAI Architects, and Business teams to pilot use cases and discuss engineering design and implementation.
Selecting appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Supporting the successful execution and operational improvement of AI-powered applications using agile methodology.
Working closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Assisting project teams with technical review boards and design authority approvals, ensuring compliance with data privacy, security and regulatory requirements in AI solution design and implementation.
Developing and maintaining contact with client stakeholders and contributing to proposal development.
Managing diverse teams within an inclusive team culture where people are recognised for their contribution and developing the capability of junior team members through training and formal development programmes on the job.
Qualifications
Proven experience of software/data engineering with proven track record focused on applied AI engineering, using Python and SQL (ML engineering experience preferred).
Demonstrate experience across the Financial Services industry, with a primary focus on the Banking sector.
Have experience designing Agentic AI solutions, managing and sequencing scopes, estimating the build effort and dependencies, and thinking commercially about AI systems to estimate or measure return on investment.
Have exposure to software delivery methodologies and tooling - Agile/SaFe, Extreme Programming, Jira, Confluence, Linear, Monday.
Demonstrate experience of LLM fundamentals: prompt engineering, fine-tuning, embedding models and RAG patterns.
Demonstrate experience working with at least 1 vector database product (e.g. Pinecone), experience working with an agent framework (e.g. LangChain, LangGraph, Agent Development Kit), and experience using MCP.
Be knowledgeable in designing and building evaluation frameworks for agentic systems and comfortable building API-enabled backend services (e.g. FastAPI).
Demonstrate a strong understanding of modern data architectures and be abel to proactively identify technical and delivery risks.
Be comfortable using common CI/CD tooling, including setting up CI/CD pipelines for ML Engineering or Agent Development.
Demonstrate MLOps or LLMOps knowledge and experience.
Demonstrate experience working with at least 1 hyperscaler stack, cloud certifications preferred (AWS, Azure, GCP, or Databricks).
Demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams.
Show and ability to bring teams together and lead technical programmes to drive success through applying coaching, facilitation, stakeholder management and expectation management capabilities.
Have strong communication and collaboration abilities, with the capability to work effectively with cross-functional teams and stakeholders.
Be able to contribute to 'go-to-market' activities such as bids, responding to requests for proposals, and developing high-quality proposal materials.
Hybrid Working Policy
You’ll be based in London with hybrid working. Depending on the requirements of your role, you’ll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You’ll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritise your wellbeing. Please check with your recruiter about the specific working requirements that may apply for your role.
Personal Independence
Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (in relation to any financial interests and employment relationships). This can mean that you and your “Immediate Family Members” are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further details as you progress through the recruitment process, or you can contact the Independence team upon request.
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As an AI Engineer, your role will be to develop the AI engineering strategy, supporting our Banking clients to design, implement, and operate scalable AI solutions across their businesses, playing a critical role in designing, implementing, and integrating AI solutions with existing enterprise systems.
Key Responsibilities
Translating the vision of senior client stakeholders and senior Deloitte AI engineers into a delivery and implementation roadmap, ensuring alignment with strategic goals and digital transformation efforts.
Collaborating with Enterprise, Application, Data, and DevOps Architects, Data Scientists, MLOps and GenAI Architects, and Business teams to pilot use cases and discuss engineering design and implementation.
Selecting appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Supporting the successful execution and operational improvement of AI-powered applications using agile methodology.
Working closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Assisting project teams with technical review boards and design authority approvals, ensuring compliance with data privacy, security and regulatory requirements in AI solution design and implementation.
Developing and maintaining contact with client stakeholders and contributing to proposal development.
Managing diverse teams within an inclusive team culture where people are recognised for their contribution and developing the capability of junior team members through training and formal development programmes on the job.
Qualifications
Proven experience of software/data engineering with proven track record focused on applied AI engineering, using Python and SQL (ML engineering experience preferred).
Demonstrate experience across the Financial Services industry, with a primary focus on the Banking sector.
Have experience designing Agentic AI solutions, managing and sequencing scopes, estimating the build effort and dependencies, and thinking commercially about AI systems to estimate or measure return on investment.
Have exposure to software delivery methodologies and tooling - Agile/SaFe, Extreme Programming, Jira, Confluence, Linear, Monday.
Demonstrate experience of LLM fundamentals: prompt engineering, fine-tuning, embedding models and RAG patterns.
Demonstrate experience working with at least 1 vector database product (e.g. Pinecone), experience working with an agent framework (e.g. LangChain, LangGraph, Agent Development Kit), and experience using MCP.
Be knowledgeable in designing and building evaluation frameworks for agentic systems and comfortable building API-enabled backend services (e.g. FastAPI).
Demonstrate a strong understanding of modern data architectures and be abel to proactively identify technical and delivery risks.
Be comfortable using common CI/CD tooling, including setting up CI/CD pipelines for ML Engineering or Agent Development.
Demonstrate MLOps or LLMOps knowledge and experience.
Demonstrate experience working with at least 1 hyperscaler stack, cloud certifications preferred (AWS, Azure, GCP, or Databricks).
Demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams.
Show and ability to bring teams together and lead technical programmes to drive success through applying coaching, facilitation, stakeholder management and expectation management capabilities.
Have strong communication and collaboration abilities, with the capability to work effectively with cross-functional teams and stakeholders.
Be able to contribute to 'go-to-market' activities such as bids, responding to requests for proposals, and developing high-quality proposal materials.
Hybrid Working Policy
You’ll be based in London with hybrid working. Depending on the requirements of your role, you’ll have the opportunity to work in your local office, virtual collaboration spaces, client sites and remotely. You’ll get the chance to meet face to face when needed, while you collaborate and learn from colleagues, share your experiences, and build the relationships that will fuel your career and prioritise your wellbeing. Please check with your recruiter about the specific working requirements that may apply for your role.
Personal Independence
Regulation and controls are standard practice in our industry and Deloitte is no exception. These controls provide important legal protection for both you and the firm. We are subject to a number of audit regulations, one of which requires that certain colleagues abide by specific personal independence constraints (in relation to any financial interests and employment relationships). This can mean that you and your “Immediate Family Members” are not permitted to hold certain financial interests (shares, funds, bonds etc.) with audit clients of the firm, and also prohibitions on certain employment relationships (e.g., you are not permitted to hold a secondary employment role with SEC audit clients of the firm whilst being employed by the firm). The recruitment team will provide further details as you progress through the recruitment process, or you can contact the Independence team upon request.
#J-18808-Ljbffr
Contact Details:
Hm Revenue & Customs (Hmrc) Recruitment Team
