AI/ML Platform Engineer

Role Overview: Join a forward-thinking technology team focused on building and scaling Generative AI solutions that deliver measurable business impact. As an AI/ML Developer, you will design, develop, and operationalize GenAI-powered applications using Python, FastAPI, and Azure AI Services. You will work closely with product managers, data scientists, and platform engineers to translate business requirements into production-ready AI services. Your day will involve developing APIs, integrating Large Language Models (LLMs), optimizing inference pipelines, and ensuring reliable, secure, and scalable deployments in the cloud. Key Responsibilities: - Design and develop GenAI-powered applications such as chatbots, copilots, document intelligence, summarization, and knowledge retrieval solutions. - Build and maintain scalable backend services and APIs using Python and FastAPI for AI and ML workloads. - Implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embedding generation, vector search, and prompt orchestration. - Integrate and leverage Azure AI Services, including Azure OpenAI, Azure AI Search, and other Cognitive Services as required. - Optimize model inference for latency, cost, and reliability, including caching, streaming responses, and batching strategies. - Collaborate with cross-functional teams to align AI solutions with business objectives, timelines, and quality expectations. - Ensure production readiness by implementing monitoring, logging, error handling, and security best practices. - Identify technical risks related to GenAI adoption and cloud deployments and proactively implement mitigation strategies. - Continuously improve AI development workflows through experimentation, evaluation, and incorporation of industry best practices. Qualifications Required: - Degree in software engineering, machine learning engineering, or applied AI development. - Strong hands-on experience with Python and backend development using FastAPI. - Proven experience building and deploying Generative AI / LLM-based applications in production environments. - Practical experience with Azure AI Services, especially Azure OpenAI and Azure AI Search (vector or hybrid search). - Solid understanding of RAG architectures, prompt engineering, embeddings, and LLM integration patterns. - Experience working with REST APIs, authentication mechanisms, and secure service-to-service communication. - Familiarity with databases, object storage, and vector databases or vector indexing solutions. - Ability to work in agile teams, communicate effectively with technical and non-technical stakeholders, and deliver results independently. - Detail-oriented, results-driven mindset with strong problem-solving and ownership skills. (Note: The additional details of the company were not included in the provided job description.) Role Overview: Join a forward-thinking technology team focused on building and scaling Generative AI solutions that deliver measurable business impact. As an AI/ML Developer, you will design, develop, and operationalize GenAI-powered applications using Python, FastAPI, and Azure AI Services. You will work closely with product managers, data scientists, and platform engineers to translate business requirements into production-ready AI services. Your day will involve developing APIs, integrating Large Language Models (LLMs), optimizing inference pipelines, and ensuring reliable, secure, and scalable deployments in the cloud. Key Responsibilities: - Design and develop GenAI-powered applications such as chatbots, copilots, document intelligence, summarization, and knowledge retrieval solutions. - Build and maintain scalable backend services and APIs using Python and FastAPI for AI and ML workloads. - Implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embedding generation, vector search, and prompt orchestration. - Integrate and leverage Azure AI Services, including Azure OpenAI, Azure AI Search, and other Cognitive Services as required. - Optimize model inference for latency, cost, and reliability, including caching, streaming responses, and batching strategies. - Collaborate with cross-functional teams to align AI solutions with business objectives, timelines, and quality expectations. - Ensure production readiness by implementing monitoring, logging, error handling, and security best practices. - Identify technical risks related to GenAI adoption and cloud deployments and proactively implement mitigation strategies. - Continuously improve AI development workflows through experimentation, evaluation, and incorporation of industry best practices. Qualifications Required: - Degree in software engineering, machine learning engineering, or applied AI development. - Strong hands-on experience with Python and backend development using FastAPI. - Proven experience building and deploying Generative AI / LLM-based applications in production environments. - Pr