SENIOR AI PLATFORM ENGINEER

Senior AI Platform Engineer

Applied AI 5-6 years of relevant experience

Role purpose

Architect and evolve the reusable platform capabilities that enable engineering teams to build deploy govern and scale secure production-grade AI agents and LLM-powered applications.

Job Summary

We are seeking an experienced Senior AI Platform Engineer with 5-6 years of relevant backend platform distributed systems or applied AI engineering experience. The role will own key architectural and technical decisions for the organizations AI platform building reusable frameworks orchestration capabilities model and tool integrations and operational controls for production-grade AI systems. The successful candidate will work across engineering architecture security and product teams to establish standards and accelerate the delivery of reliable observable secure and scalable AI-powered solutions.

Key Responsibilities

• Design develop and evolve the core architecture of the shared AI platform used to build and deploy AI agents and LLM-powered services.
• Architect and implement agent orchestration frameworks using LangChain LangGraph or comparable technologies for complex stateful and multi-step AI workflows.
• Develop and maintain platform SDKs Python libraries templates APIs and developer tooling that standardize integration with models tools data sources and enterprise systems.
• Own the LLM integration layer supporting multiple commercial providers locally hosted models embedding services vector stores and internal AI services.
• Design platform capabilities for prompt lifecycle and configuration management tool calling memory and state handling agent execution evaluation and model routing.
• Implement observability tracing and evaluation capabilities using Langfuse or equivalent platforms to monitor prompts agent execution latency quality token usage cost and system performance.
• Architect retrieval-augmented generation (RAG) capabilities including ingestion indexing retrieval reranking grounding and evaluation patterns.
• Ensure the platform meets production requirements for scalability availability resilience security privacy and performance through sound engineering and operational practices.
• Partner with Applied AI Engineers architects security teams and product owners to define reusable patterns development standards and platform guardrails.
• Lead technical design reviews influence the platform roadmap maintain architectural documentation and drive automated testing CI/CD and release quality.
• Mentor junior engineers provide technical guidance and promote engineering excellence across the AI platform team.

Required Skills and Qualifications

• 5-6 years of relevant experience in backend engineering platform engineering distributed systems or applied AI development.
• Advanced Python programming skills including experience building platform frameworks SDKs APIs and reusable packages.
• Hands-on experience designing and building LLM-powered platforms AI infrastructure agent-based systems or production generative AI services.
• Strong practical experience with LangChain LangGraph or similar agent and workflow orchestration frameworks.
• Deep understanding of prompt engineering RAG architectures embeddings retrieval and reranking tool integration memory and agent workflows.
• Proven experience designing microservices asynchronous processing patterns APIs and scalable distributed systems.
• Strong command of software engineering practices including design patterns automated testing code review CI/CD and containerization.
• Strong understanding of logging monitoring distributed tracing evaluation and performance management for AI systems.
• Bachelors degree in Computer Science Software Engineering Artificial Intelligence or a related discipline or equivalent practical experience.

Preferred Qualifications

• Experience designing vector database semantic search and enterprise retrieval pipelines.
• Experience implementing AI observability and evaluation using Langfuse LangSmith or equivalent tools.
• Experience integrating multiple LLM providers and self-hosted or open-source models including routing and fallback patterns.
• Experience building internal AI platforms reusable Python frameworks or developer tooling used by multiple engineering teams.
• Experience with Docker Kubernetes cloud-native architectures infrastructure automation and secure secrets and API management.
• Knowledge of responsible AI model governance data privacy access control and enterprise security requirements.

Key Competencies

• System design: Translates complex requirements into coherent scalable and maintainable platform architectures.
• Platform thinking: Builds reusable capabilities paved roads and standards that improve engineering productivity.
• Technical leadership: Leads design decisions mentors engineers and raises engineering standards through influence and example.
• Ownership and reliability: Owns production readiness resilience maintainability and continuous improvement.
• Collaboration and communication: Communicates architectural decisions clearly and aligns stakeholders across engineering product security and operations.

Location: Abu Dhabi UAE (on-site) Duration: 3 months Start: ASAP subject to security clearance Language: Arabic speakers preferred

Vertical

Technology