Job Description
We are looking for a Senior AI Engineer to lead the evolution of our RPA (Robotic Process Automation) systems into next-generation Agentic AI architectures. This role demands deep expertise in AI model development, intelligent agent design, and enterprise integration to build autonomous, self-learning solutions that drive efficiency and adaptability across business processes. Technical Skills Tools Core AI ML Python, PyTorch, TensorFlow, or JAX for model development. Experience with LLMs, RAG (Retrieval-Augmented Generation), and Agentic AI frameworks (LangChain, AutoGen, Semantic Kernel, CrewAI). Strong knowledge of transformer architectures, prompt engineering, and orchestration. Automation Integration Familiarity with RPA tools (e.g., UiPath) and AI-driven migration paths. Expertise in API integration, event-driven systems, and microservices. Experience with workflow orchestration tools (e.g., Azure Logic Apps). Data Engineering MLOps Data preprocessing, feature engineering, and deployment using MLflow, Kubeflow, or Vertex AI. Experience with vector databases (Pinecone, Weaviate, FAISS) and embedding techniques. Proficiency with Azure AI Services or similar platforms. Knowledge of Docker, Kubernetes, and CI/CD pipelines for model lifecycle automation. Preferred Skills Familiarity with ethical AI frameworks and governance standards. Hands-on experience with LLM fine-tuning, function calling, and agent memory design. Strong problem-solving, leadership, and communication skills.
Qualifications Experience
Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, or related field. 5 8+ years of experience in AI/ML development, with at least 2+ years focused on LLMs or Agentic AI systems. Proven track record of designing and deploying enterprise-scale AI solutions. Experience leading AI modernization initiatives in cross-functional environments.
Key Responsibilities
Lead the migration of RPA bots into Agentic AI systems with minimal disruption. Analyze operational data from RPA bots to identify optimization opportunities. Design, build, and deploy intelligent agents for complex workflows and decision-making. Train and fine-tune AI models to ensure accuracy, reliability, and scalability. Integrate Agentic AI systems with enterprise tools, APIs, and databases. Architect scalable AI solutions to support future growth and workload expansion. Monitor and maintain deployed AI agents, applying continuous improvements. Ensure compliance with ethical AI standards (fairness, transparency, privacy). Collaborate with AI Analysts and cross-functional teams to gather requirements and validate outcomes. Drive pilot projects, ensuring delivery aligns with success criteria. Champion continuous improvement through performance analysis and