AI Engineer – LLM Systems & Cloud Platform

About the role

We are looking for an AI Engineer to design, build and operate large-language-model (LLM) solutions and cloud-native AI platforms for domain-specific tasks. The role combines applied AI research, production engineering, and team leadership in a fast-growing ICT environment.

Key responsibilities

• Build, fine-tune and evaluate LLMs (e.g., Llama-3, Mistral) using QLoRA/PEFT for business use cases.
• Design reproducible evaluation harnesses and A/B testing frameworks with metrics such as task success rate, safety rate and latency.
• Architect multi-agent and Retrieval-Augmented Generation (RAG) systems with LangGraph, FastAPI and vector databases.
• Implement safety guardrails, input/output validation and allow-list/deny-list policies.
• Translate business requirements into deployable prototypes and demo them to stakeholders.
• Design, provision and operate cloud infrastructure and MLOps workspaces on Azure, OCI or GCP using Kubernetes and container runtimes.
• Build CI/CD pipelines and GitOps-based release processes (Argo CD, Azure DevOps, GitHub Actions).
• Implement end-to-end observability (Azure Monitor, Application Insights, ELK) and security baselines (FW/WAF, SonarQube, Black Duck).
• Own disaster-recovery design, automated backups and documented RTO/RPO commitments.
• Lead and mentor a cloud/AI operations team, define monitoring, incident response and release governance.
• Standardize SDLC practices, consolidate tooling and produce handover documentation and runbooks.
• Support vendor and licensing negotiations for cloud enterprise agreements.

Required profile

• Bachelor’s degree in Software Engineering, Computer Science or related field.
• 6-8+ years of software, DevOps or platform engineering experience, including at least 2 years in applied AI/ML.
• Proven delivery of production-grade AI/LLM systems.
• Strong Python programming skills; comfortable with Bash and YAML.
• Deep hands-on experience with Kubernetes, Docker/Podman and Terraform.
• Production experience on a major cloud platform (Azure preferred, OCI or GCP acceptable).
• Ownership of CI/CD pipelines at scale and GitOps release models.
• Experience leading engineering teams and setting standards across squads.

Required skills

• Python, Bash, YAML
• Kubernetes, Docker, Podman, Terraform
• Azure, OCI, GCP
• Azure DevOps, GitHub Actions, Argo CD
• FastAPI, PyTorch, Transformers, LangGraph
• QLoRA/LoRA fine-tuning
• Milvus, Pinecone, Weaviate (vector databases)
• Redis, PostgreSQL
• ELK, Azure Monitor, Application Insights
• SonarQube, Black Duck, Fortinet FW/WAF