AI Engineer – Generative AI & Agentic AI

We are looking for an experienced AI Engineer responsible for designing, developing, and deploying Generative AI and Agentic AI solutions that support enterprise\-scale business use cases. The role will build intelligent systems that integrate complex backend services and client\-facing applications across web, mobile and enterprise platforms. The primary responsibility is to design and develop AI\-powered applications, autonomous agents and multi\-agent workflows while coordinating with cross\-functional teams across architecture, engineering, product and business functions. A commitment to collaborative problem solving, sophisticated design and product quality is essential. This role requires strong hands\-on engineering experience, practical working knowledge of modern agent frameworks, and the ability to deliver secure, scalable, observable and governed AI solutions in cloud\-native environments. **QUALIFICATIONS \& EXPERIENCE:** **Minimum Qualification** * Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or a related discipline. * Relevant cloud, AI engineering, machine learning or architecture certifications are preferred. **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. **Behavioural / Leadership Skills** * Strong collaborative mindset for agile architecture and decentralized decision making. * Proactive, positive and growth\-oriented leadership style with the ability to motivate engineers and foster craftsmanship. * Strong communication, stakeholder engagement and influencing skills across product, business, architecture and engineering teams. * Analytical, system\-thinking and pragmatic problem\-solving approach with commitment to product quality. **Skills:** Generative AI , Python , Kubernetes