Absa Group

AI Platform Engineer (Cloud)

Absa Group

Kenya · Full Time

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Experience
Any
Salary
Openings
1
Posted
hace 4 horas
Work mode
In office
Education
Bachelor's degree
Resume
Required to apply

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Job description

About Absa Group and Career Growth

Absa Group is a well-established local bank with a heritage spanning over 100 years, combining regional and international expertise. Joining Absa offers the chance to contribute to a transformative growth journey and be part of shaping the future of a proudly African financial group. Through its Career Development Portal, Absa supports employees at every career stage with guidance, tools, and resources to unlock their full potential.

Job Summary

The Chief Data Analytics and Applied AI Office (CDAIO) at Absa Group is looking for an experienced AI Platform Engineer specializing in cloud technologies. This position involves the design, deployment, operation, and continuous refinement of a multi-cloud infrastructure that underpins the enterprise AI capabilities across multiple business units and countries, including Corporate and Investment Banking, Personal and Private Banking, Business Banking, and Absa Regional Operations.

The role requires practical expertise in cloud platform engineering, infrastructure as code, AI workload deployment, observability, cost optimization, security, and managing agentic AI infrastructure. Collaboration with senior engineers, architects, security teams, FinOps specialists, and AI solution engineers is essential to ensure platform services align with architecture, security, risk, and responsible AI guidelines.

Key Responsibilities

  • Support the design and operational management of multi-cloud AI infrastructure, including AWS Bedrock, Databricks AI, Microsoft Azure AI Foundry, Hugging Face, Kubernetes, and GPU clusters.
  • Create and maintain reusable platform components such as AI Gateway configurations, model serving environments, API integrations, vector databases, data pipelines, and containerized workloads.
  • Develop infrastructure as code using Terraform, Pulumi, AWS CDK, or similar tools to enable repeatable, auditable infrastructure across cloud environments and regions.
  • Manage agentic AI infrastructure, including orchestration frameworks, tool-calling APIs, agent memory, and integration with enterprise systems.
  • Implement cloud-agnostic serving patterns to enhance workload portability across AWS, Azure, Databricks, and Kubernetes environments.
  • Monitor AI platform resource consumption for cost management and optimization, supporting development of chargeback and cost reports using tools like AWS Cost Explorer, Databricks System Tables, and Azure Cost Management.
  • Maintain platform observability through dashboards and alerts focusing on inference latency, platform availability, throughput, model health, GPU utilization, and capacity management using technologies like Prometheus, Grafana, Datadog, and OpenTelemetry.
  • Ensure AI platform security by implementing zero-trust controls, authentication and authorization mechanisms (OAuth 2.0, OpenID Connect, JWT/JWE/JWS, RBAC, ABAC), and data protection measures compliant with regulatory requirements and Absa’s policies.
  • Support deployment and management of agent orchestration technologies and secure tool-calling patterns for agentic AI workloads.
  • Participate actively in agile development processes including sprint planning, reviews, and retrospectives, collaborating with multidisciplinary teams to deliver platform features and improvements.
  • Maintain technical documentation, architectural designs, operational runbooks, and support knowledge sharing and guidance for junior engineers.
  • Continuously update knowledge of emerging cloud AI platforms, MLOps, FinOps, AI security, and platform engineering best practices.

Qualifications and Experience

  • Bachelor’s degree in Computer Science, IT, Data Science, Mathematics, Statistics, Engineering, or a related quantitative field is mandatory.
  • Postgraduate qualifications are beneficial.
  • Relevant hands-on experience in cloud platform engineering and delivering infrastructure solutions is valued.
  • Certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning Engineer, Microsoft Certified Azure AI Engineer Associate, and Microsoft Certified Azure Solutions Architect Expert are advantageous.

Minimum education

Bachelor's Degree

Tools & software

Kubernetes required

How they work

Teamwork & Collaboration Problem Solving Attention to Detail Adaptability

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