Senior Applied AI Engineer

Detailed Job Description

Company Overview Our client a consulting major, is looking for strong technical application development expertise. Position Overview As an Applied AI Engineer, you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business and its users. Responsibilities • Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. • Possess expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate strong understanding of the full lifecycle product development, focusing on continuous improvement and learning. • Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Skills & Experience • 6+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks. • 3+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration. • 3+ years of experience with cloud-native engineering, using FaaS, PaaS, or micro-services on cloud hyperscalers such as AWS including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability).