AI Engineer – Python, Generative AI, LLM/RAG, Cloud AI & MLOpsMLOps & Kubernetes

Job Summary Synechron is seeking an AI Engineer to design, develop and the implementation of Artificial Intelligence, Machine Learning and Generative AI solutions. The role will combine hands-on software engineering with technical leadership across machine learning models, LLM-based applications, data pipelines, cloud AI services and production-grade AI platforms. The AI Tech Lead will translate business and technical requirements into scalable AI-driven solutions, guide architecture decisions, mentor AI/ML engineers and collaborate with stakeholders to deliver reliable, secure and maintainable products. This is a full-time position based in Pune, suitable for professionals with 6–8 years of experience in software development, artificial intelligence or machine learning. Software Requirements Required Python: Strong proficiency for AI/ML development, data processing, model development and production applications; experience with the project-supported version. TensorFlow, PyTorch and Scikit-learn: Hands-on experience developing, optimizing and evaluating machine learning and deep learning models. Generative AI and LLMs: Experience developing LLM-based applications, including prompt engineering, Retrieval-Augmented Generation (RAG) and AI agents. Cloud AI Services: Hands-on experience with one or more of the following:Azure AIAzure OpenAIAWS AI/ML servicesGoogle Cloud AI services Vector Databases: Experience storing, indexing and retrieving embeddings for AI and RAG applications. LangChain, Semantic Kernel or Similar Frameworks: Practical experience building LLM applications, orchestration workflows or AI agents. APIs and Microservices: Experience designing or integrating APIs and microservices for AI-enabled applications. Docker and Kubernetes: Experience containerizing, deploying and managing AI/ML applications. CI/CD Pipelines: Experience integrating software and model delivery into automated build, test and deployment pipelines. SQL and NoSQL Databases: Experience working with structured and unstructured data stores. Large-Scale Data Processing: Experience developing or supporting data pipelines for AI/ML solutions. MLOps: Experience with model deployment, monitoring, versioning, reliability and operational support. Preferred Experience with AI governance, responsible AI practices and model monitoring. Experience leading technical teams or AI/ML projects. Certification in Azure AI, AWS Machine Learning or equivalent cloud technologies. Experience with enterprise-scale Generative AI platforms and production LLM applications. Experience with model optimization, evaluation frameworks, observability and cost management. Experience implementing reusable AI platforms and shared services. Overall Responsibilities Lead the design, development and deployment of AI/ML and Generative AI solutions. Architect scalable AI platforms that meet functional, performance, security, reliability and maintainability requirements.