Lead AI Engineer

We are seeking an accomplished Lead AI Engineer to design, develop, and implement AI-driven solutions within our software development lifecycle.

You will lead enterprise-scale AI integration initiatives, establish best practices, and advance the technical maturity of our engineering organization.

AI Engineering & Implementation

• Lead the design and development of 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 advanced 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 models

AI-Driven Software Development Lifecycle (SDLC)

• Implement AI spec-driven development practices for your squad
• Contribute to AI/ML solutions that enhance code generation, testing, deployment, and monitoring
• Integrate AI technologies into existing SDLC workflows and development tooling
• Collaborate on governance and responsible AI implementation

Technical Leadership & Collaboration

• Lead technology evaluation and assessment for organizational adoption
• Collaborate with enterprise architecture, security, and compliance teams on AI integration
• Contribute to technical training and knowledge-sharing initiatives across the organization

What You Need to Succeed

• 10+ years of experience building and operating production software systems at scale
• 2–4 years of hands-on experience with LLMs and generative AI in production environments
• Expert proficiency in .NET/C#, Java, Python, SQL, Git, and CI/CD pipelines
• Deep knowledge of design patterns (MVC, MVVM), SOA, and architectural concepts; hands-on development experience with Azure Integration Services
• Expert-level expertise in API architecture (REST/SOAP)
• Advanced working knowledge of agentic AI patterns: tool use, agent orchestration, ReAct, multi-step reasoning, memory and context management
• Proven proficiency in LLM API integration, prompt engineering, and RAG systems (vector databases, embeddings, retrieval strategies)
• Demonstrated experience designing and building MCP servers and tools with agent-tool integration frameworks
• Cloud platform expertise (AWS, Azure, or GCP), including containers (Docker/Kubernetes) and CI/CD pipelines
• Strong collaboration and communication skills; comfortable with code reviews, design discussions, and pair programming
• Ability to communicate technical decisions clearly to both technical peers and business stakeholders
• Understanding of security, data governance, and responsible AI practices