Senior AI Engineer

We are seeking an accomplished Senior AI Engineer to contribute to the design, development, and implementation of AI-driven solutions within our software development lifecycle. This role offers the opportunity to work on enterprise-scale AI integration initiatives, establish best practices, and advance the technical maturity of our engineering organization. Responsibilities AI Engineering & Implementation Design and build MCP (Model Context Protocol) servers and tools for seamless AI integration Design and implement AI-driven automation solutions, including LLM-powered automation, prompt engineering, and conversational AI Develop ML model integration solutions and AI orchestration workflows with monitoring and evaluation Integrate UiPath with enterprise AI platforms and APIs Support implementation of agentic automation and advanced AI use cases AI/ML Expertise & Governance Integrate LLM APIs and apply prompt engineering techniques Design and maintain AI workflow orchestration systems Implement Intelligent Document Processing and NLP solutions Develop model evaluation, tuning, and governance frameworks Design and manage vector databases and RAG (Retrieval-Augmented Generation) systems Support responsible AI practices and governance model development AI-Driven Software Development Lifecycle (SDLC) Contribute to AI/ML solutions that enhance code generation, testing, deployment, and monitoring Integrate AI technologies into existing SDLC workflows and development tooling Support development and implementation of governance models for AI and responsible AI practices Technical Contributions & Collaboration Participate in technology evaluation and assessment for organizational adoption Collaborate with enterprise architecture, security, and compliance teams on AI initiatives Contribute to technical training and knowledge-sharing initiatives Support code reviews, design discussions, and mentoring of junior team members Requirements 4–6 years of experience building and operating production software systems at scale 1–2 years of hands-on experience with LLMs and generative AI in production environments or serious prototyping Proficiency in .NET/C#, Python, SQL, Git, and CI/CD pipelines Strong expertise in API architecture (REST/SOAP) Solid working knowledge of agentic AI patterns: tool use, agent orchestration, ReAct, multi-step reasoning, memory and context management Proven proficiency in LLM API integration and prompt engineering Cloud platform experience (AWS, Azure, or GCP), including containers (Docker/Kubernetes) and CI/CD pipelines Experience building or contributing to RAG systems (vector databases, embeddings, retrieval strategies) Demonstrated experience designing and building MCP servers and tools with familiarity of agent-tool integration frameworks Strong collaboration and communication skills; comfortable with code reviews, design discussions, and pair programming Ability to explain technical decisions clearly to both technical peers and business stakeholders Understanding of security, data governance, and responsible AI practices Benefits Comprehensive Total Rewards Program including competitive compensation, bonuses, flexible benefits, commissions, and stock options where applicable Development-focused leadership committed to your growth through coaching and career opportunities Opportunity to make a meaningful, lasting impact on enterprise AI adoption Dynamic, collaborative, and high-performing team environment World-class training programs in financial services and emerging technologies Job Data by YubHub .