- Company Name
- Cloud Bridge
- Job Title
- AI Augmented Engineering Lead - Up to £130k + Bonus
- Job Description
-
Job Title: AI Augmented Engineering Lead
Role Summary: Lead integration of AI‑driven tools into an AWS‑based DevSecOps platform to boost developer productivity, software quality, and delivery velocity. Drive platform evolution, define AI guardrails, and mentor engineering teams.
Expactations: Deliver secure, high‑quality software at scale; reduce lead time, defect rates, and improve developer experience; implement AI tools and policies; manage AWS infrastructure; collaborate across functions; mentor staff.
Key Responsibilities:
- Evaluate and implement AI tools for coding assistance, automated testing, quality, incident analysis, and operational insights.
- Define and enforce secure, responsible AI usage guardrails and standards.
- Design, build, and optimize AWS‑based infrastructure (Bedrock, Serverless) using CDK/Terraform.
- Build and refine CI/CD pipelines with embedded security, quality, and policy controls.
- Enhance observability through AI‑assisted monitoring, alerting, and root‑cause analysis.
- Measure AI adoption impact with metrics such as lead time, defect rates, pipeline efficiency, developer experience.
- Translate emerging AWS services and AI capabilities into production solutions.
- Collaborate with cross‑functional teams to embed generative AI into existing systems.
- Lead, mentor, and support engineering teams.
Required Skills:
- Proficiency in AI/ML, generative AI, and large language models (LLMs).
- Hands‑on experience with Python, JavaScript, React.js.
- Deep AWS expertise (Bedrock, Serverless, automation, security best practices).
- Infrastructure‑as‑Code with CDK and Terraform.
- DevOps practices: CI/CD, SCM, Docker, Kubernetes.
- Monitoring/logging tools: Grafana, CloudWatch, Prometheus, ELK Stack.
- Cloud security and compliance knowledge.
- Strong troubleshooting, analytical, and problem‑solving skills.
- Leadership, project management, and mentorship capabilities.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- Relevant certifications: AWS Certified Solutions Architect, AWS Certified DevOps Engineer, or equivalent.
- Experience with LLM frameworks (e.g., OpenAI, Anthropic) preferred.