Agentic AI Engineer
Exiger
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchTensorflow
Senior Machine Learning Engineer
BT Group
full-time
Posted on:
Location Type: Hybrid
Location: London • 🇬🇧 United Kingdom
Visit company websiteJob Level
Senior
Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformPythonSQLTerraform
About the role
- Lead, mentor, and develop your engineering team, fostering a culture of learning and collaboration.
- Architect and build on BT’s MLOps stacks for fast, safe, and scalable ML/GenAI delivery with clear FinOps guardrails.
- Design and implement production-grade ML/AI infrastructure, championing reusable patterns and best practices with Data Scientists, support, and engineering teams.
- Embed FinOps, security, and data privacy into every stage of the ML/AI lifecycle.
- Work closely with data scientists, engineers, and stakeholders to accelerate research-to-production using robust engineering practices and AI coding tools.
- Define support strategies for long-term model health, including SLOs, drift monitoring, and feedback loops.
- Lead deployment of LLM and GenAI services on platforms like Amazon Bedrock and Google Vertex AI.
- Design and translate infrastructure for GenAI applications: vector databases, embeddings, retrieval/RAG, model gateways, GPU management, observability, and cost monitoring.
- Promote experiment tracking and model management tools (e.g., Weights & Biases).
- Ensure strong software engineering practices: code review, testing, documentation, and version control.
Requirements
- Bachelor’s degree, MSc, or equivalent in Computer Science, Engineering, Mathematics, or related field.
- Professional certifications in AWS, GCP, or Azure (Architect, Engineering, or ML) are highly desirable.
- Solid experience in ML/AI engineering, cloud engineering, or MLOps
- Deep expertise in at least one major cloud platform (AWS, GCP, or Azure); knowledge of Vertex AI or equivalent required.
- Proven experience building, debugging, and deploying ML pipelines for large-scale, high-throughput, low-latency applications.
- Production-level fluency managing components in Python, Docker, and deploying ML/AI services (e.g., FastAPI).
- Supporting skills in SQL and advanced use of Terraform, Pulumi, or AWS CDK.
- Advanced expertise in CI/CD pipelines (GitLab CI, GitHub Actions) and MLOps pipelining services (Kubeflow, TFX, Kedro, or MLflow).
- Practical experience deploying LLMs and other AI models, with understanding of sourcing, performance, quantization, batching, inference service management, metrics, and design trade-offs.
- Demonstrated experience managing FinOps, security, and data privacy in ML/AI systems.
- Experience leading, mentoring, and developing a positive engineering team culture.
Benefits
- Competitive salary
- 25 days annual leave (plus bank holidays)
- 10% on target bonus
- Life Assurance
- Pension scheme
- Direct share scheme
- Option to join the Healthcare Cash Plan or other benefits such as dental insurance, gym memberships etc.
- 50% off EE mobile pay monthly or SIM only plans
- Exclusive colleague discounts on our latest and greatest BT broadband packages
- BT TV with TNT Sports and NOW Entertainment
- 50% discount for friends and family on EE SIM Only plans & airtime element off a Flex Pay plan
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
ML engineeringAI engineeringMLOpscloud engineeringPythonDockerSQLTerraformCI/CD pipelinesLLM deployment
Soft skills
leadershipmentoringcollaborationcommunicationteam developmentproblem-solvingorganizational skillsculture buildingstakeholder engagementsupport strategy definition
Certifications
AWS certificationGCP certificationAzure certification