Job Title: AI Platform EngineerJob Summary We are looking for an AI Platform Engineer to design, build, and maintain scalable AI infrastructure and platforms that enable data scientists and machine learning engineers to develop, deploy, monitor, and manage AI/ML models efficiently. The ideal candidate has strong experience with cloud platforms, MLOps, containerization, automation, and modern AI technologies.
Key Responsibilities - Design, develop, and maintain AI/ML platforms and infrastructure.
- Build scalable MLOps pipelines for model training, deployment, monitoring, and retraining.
- Develop CI/CD workflows for machine learning applications.
- Manage Kubernetes clusters and containerized AI workloads.
- Implement model serving, feature stores, model registries, and experiment tracking solutions.
- Optimize GPU infrastructure and distributed training environments.
- Integrate Large Language Models (LLMs), vector databases, and AI frameworks into enterprise platforms.
- Monitor platform performance, reliability, scalability, and security.
- Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams.
- Implement Infrastructure as Code (IaC) using tools such as Terraform.
- Ensure platform governance, compliance, and cost optimization.
- Troubleshoot production AI platform issues and improve operational efficiency.
Required Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 4+ years of experience in Platform Engineering, DevOps, MLOps, or Cloud Engineering.
- Strong programming skills in Python.
- Experience with Docker and Kubernetes.
- Hands-on experience with AWS, Azure, or Google Cloud Platform.
- Experience building CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins.
- Experience with Terraform or similar Infrastructure as Code tools.
- Knowledge of Linux systems and networking.
- Experience with monitoring tools such as Prometheus and Grafana.
- Familiarity with distributed systems and scalable architectures.
Preferred Qualifications - Experience with ML platforms such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
- Experience deploying and managing Large Language Models (LLMs).
- Knowledge of vector databases such as Pinecone, Milvus, Weaviate, or Chroma.
- Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
- Experience with distributed training frameworks and GPU optimization.
- Knowledge of Apache Airflow, Kafka, Spark, or Ray.
- Familiarity with security best practices for AI infrastructure.
Technical Skills - Python
- Docker
- Kubernetes
- Terraform
- Git
- CI/CD
- AWS / Azure / GCP
- MLflow
- Kubeflow
- SageMaker / Vertex AI / Azure ML
- LangChain
- LlamaIndex
- Vector Databases
- Linux
- Prometheus
- Grafana
- PostgreSQL
- Redis
Soft Skills - Strong problem-solving and analytical skills
- Excellent communication and collaboration
- Ownership and accountability
- Ability to work in Agile environments
- Continuous learning mindset
Nice to Have - Experience with Generative AI applications
- Experience with Retrieval-Augmented Generation (RAG)
- Knowledge of AI governance and Responsible AI practices
- AI platform cost optimization experience
- Relevant cloud or Kubernetes certifications
Location Hybrid / Remote / On-site (as applicable)
Employment Type Full-time
