Director AI Platform & Engineering

Hays plc

5 days ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.totaljobs.com

Tech stack

Microsoft Access Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Cloud Computing Continuous Integration Identity and Access Management Python (Programming Language) Regression Testing Systems Integration Data Logging Large Language Models

+7 more

Snowflake AI Platforms Infrastructure Automation Frameworks Virtual Agents Cloudwatch Terraform Software Version Control

Job description

The Director, Agentic AI Platform & Engineering owns the technical platform on which the businesses’ AI agents are built and operated: the AWS-based agentic automation stack (Amazon Bedrock / AgentCore and related services). This is a hands-on engineering role reporting to the Senior Director, Head of Artificial Intelligence, and does not currently have direct reports.

The role works through existing functions rather than duplicating them: Infrastructure for AWS accounts, networking, and cloud operations; Security for identity, access, and data protection; and Data / enterprise systems teams for Snowflake and system integrations., * Own the internal implementation and architecture of Amazon Bedrock / AgentCore and related AWS services as the businesses single enterprise agentic automation platform.

Design and own runtime governance components: guardrails, evaluation harnesses, automated regression testing, observability, logging, and prompt/tool/model versioning.
Build and maintain reusable agent templates and platform engineering patterns so new agents are faster, cheaper, and safer to deliver.
Own the tool/action architecture, including APIs and Lambda / Step Functions / EventBridge patterns, ensuring agents access enterprise systems through narrow, approved tools rather than broad credentials.

Requirements

10-12 years in software or platform engineering, including recent delivery of production LLM applications (RAG, tool calling, agents, evaluations).
Deep AWS expertise (IAM, Lambda, Step Functions, EventBridge, CloudWatch), infrastructure-as-code (Terraform or CDK), and CI/CD practice.
Strong proficiency in Python or a comparable language, with a sound engineering discipline.