Minimum Experience
-Senior professional with around 10 years of total software engineering, architecture, cloud or platform engineering experience.
-Minimum 3+ years of relevant hands-on AI Engineering experience, including Generative AI and practical LLM-based application delivery.
-Strong proficiency in Python, including NumPy, pandas, FastAPI and hands-on experience with PyTorch or TensorFlow.
-Hands-on experience with LangChain and LangGraph; mandatory working experience with Microsoft Semantic Kernel and Microsoft AutoGen.
-Experience implementing RAG using embeddings, vector databases, semantic search, retrieval optimization and model evaluation techniques.
-Experience deploying and managing models using Amazon Bedrock, Azure OpenAI Service and Google Vertex AI.
-Hands-on experience with microservices, containers, APIs, event-driven architecture, cloud-native services and evolutionary architecture practices.
-Experience managing and deploying AI workloads on Kubernetes in cloud-native and/or hybrid environments.
-Experience with CI/CD tools such as Jenkins or GitLab, DevOps toolchains, configuration management and cloud/on-prem deployment pipelines.
-Experience setting up pipelines with static code analysis, requirement tagging in Jira, quality gates and release governance.
-Experience operating monitoring tools for traditional infrastructure, cloud environments and AI-enabled business applications.
-Strong hands-on problem-solving mindset with the ability to analyze trade-offs and deliver sustainable, secure and high-quality solutions.

Key Technical Skills
-Generative AI, Agentic AI, autonomous agents, multi-agent orchestration and workflow-based AI systems.
-LLMs, embeddings, vector databases, RAG, semantic search, model evaluation, guardrails, observability and AI governance.
-Semantic Kernel, AutoGen, LangChain, LangGraph and similar agent frameworks.
-Python, FastAPI, PyTorch/TensorFlow, REST APIs, microservices, serverless functions and event-driven integration.
-Azure, AWS, Kubernetes, containers, CI/CD, DevOps automation, monitoring and secure software delivery.