Sr. AI Platform Engineer

501, Fifth Avenue, Suite 805 New York, NY 10017 Job Title : Sr. AI Platform Engineer What We’re Looking for (Minimum Qualifications): 8+ years of experience as Platform Engineer ( Site Reliability / DevOps Engineer) , with at least 3+ years in AI/ML platform development ( MLOps ). Deep expertise in Python, with strong design and debugging skills. Ability to work independently and lead complex projects with Excellent problem-solving, analytical, and communication skills. Proficiency working with cloud platforms such as AWS, GCP, or Azure and familiarity with MLOps/AI DevOps tools like MLflow or Kubeflow, proficient in CI/CD , infrastructure as code (Terraform / CloudFormation). Hands-on expertise with CI/CD pipelines, model observability, and incident response for AI/ML services. Preferred Qualification: Experience implementing and optimizing Platforms supporting large language model (LLM) pipelines with frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar. Hands-on knowledge of Scaling & Setting up Vector DB platforms such as Qdrant (or other vector DBs like Pinecone, Weaviate) for semantic search and embeddings management. Exposure to MLOps tools, Ray.io , Anyscale or other distributed orchestration & inference frameworks. Experience with developing and deploying containerized applications using Docker and Kubernetes, including Helm charts and automated scaling. Understanding of LLMOps patterns — model registry, prompt versioning, and feedback loops. Responsibilities Responsibilities/What You’ll Do Platform Design and Architecture: building and operating a highly available, scalable, modular AI platform using technologies such as Qdrant, Anyscale, and Ray to support LLM orchestration, vector search, and multi-agent frameworks. Core Infrastructure Development : Build essential APIs and infrastructure to power conversational applications, AI agents, and analytics tools. LLM Operational Solutions : Implement workflows for Large Language Models, including inference pipelines, fine-tuning, caching, and evaluation for open-weight and hosted models. Deployment & Performance Optimization : Deploy AI services on AWS with Kubernetes (EKS), Lambda, and ECS, ensuring scalability and resilience while optimizing vector databases and model runtimes for cost and performance. Collaboration, Governance, & Mentorship : Partner with engineering teams, research teams to deliver production-grade, self-healing, and performance-optimized services for AI/RAG pipelines , establish governance/security standards, and mentoring junior engineers in AI infrastructure best practices & reviews. Join the TechWize Team Shape the future of IT Are you a passionate techwize looking to push the boundaries of IT? Do you thrive in a collaborative environment, solving complex problems with cutting-edge solutions? If you answered yes, then TechWize is the place for you! We're seeking talented individuals to join our dynamic team and shape the future of IT. At TechWize, you'll have the opportunity to work alongside industry experts on challenging projects, using the latest technologies to deliver innovative solutions for our clients. We offer a fast-paced environment that fosters continuous learning and professional growth. #J-18808-Ljbffr TechWize