AI Solutions Engineer

AI Solutions Engineer Hyderabad, Hybrid Responsibilities Design and implement intelligent integrations between applications and enterprise platforms. Build backend services and orchestration frameworks using Python. Create interfaces leveraging Model Context Protocol (MCP) and function-calling frameworks. Design schema-driven APIs and integration patterns. Develop and maintain AI automation pipelines and workflow orchestration services. Build context-aware AI functionality using RAG architectures and LLM-based systems. Implement and support AI evaluation frameworks and observability tooling. Design resilient service-to-service communication patterns. Deploy and maintain containerized applications and AI services in cloud environments. Contribute to MLOps and platform engineering initiatives. Collaborate closely with engineering, platform, and AI teams to deliver production-grade solutions. Required Skills and Experience 8+ years of software engineering experience with a strong focus on Python. Experience supporting machine learning or MLOps ecosystems such as Kubeflow, MLflow, SageMaker, and Terraform. Advanced experience developing RESTful APIs and OpenAPI/Swagger-based services. Proven experience integrating external APIs and enterprise platforms. Strong understanding of authentication and security frameworks including OAuth2, JWT, and secure credential management. 1 year of experience with Git, CI/CD pipelines, and cloud deployment environments. Experience utilizing observability and monitoring tools such as Prometheus, Grafana, and ELK Stack. Working knowledge of Docker, Kubernetes, ArgoCD, and containerized deployments. Familiarity with AI and RAG technologies including embedding models, vector databases, Azure Cognitive Search, Pinecone, and Weaviate. Understanding of evaluation frameworks such as Scikit-learn, PyTorch, and TensorFlow. Experience integrating AI models into production systems and contributing to AI pipeline design. Nice to Have Skills and Experience Experience working with MCP (Model Context Protocol). Experience with OpenAI integrations and enterprise AI platforms. Experience integrating AI solutions with platforms such as ServiceNow or Power Automate. Experience building and deploying at least one production chatbot or conversational AI application. Familiarity with enterprise automation and workflow platforms.