Director of Engineering – AI Apps, Agent Studio

• Lead the engineering organization responsible for AI Apps and Agent Studio




• Set the technical vision, architecture, execution model, and engineering standards for AI-powered applications and agent experiences




• Own the engineering roadmap for Agent Studio and shared AI application capabilities




• Drive architecture for production AI applications, including LLM integration, agent orchestration, tool/function calling, RAG, knowledge integration, prompt/configuration management, memory/context, and human handoff patterns




• Partner with Product Management to translate AI product strategy and customer use cases into scalable platform capabilities, technical investments, delivery plans, and measurable outcomes




• Establish engineering patterns for connecting AI agents to communications, contact center, voice, messaging, collaboration, customer data, and third-party applications




• Ensure AI applications meet enterprise expectations for security, privacy, reliability, latency, observability, cost efficiency, governance, and responsible AI behavior




• Define evaluation and quality frameworks, including automated testing, model and prompt evaluation, hallucination/error analysis, regression testing, safety controls, and production monitoring




• Create platform capabilities enabling product teams and authorized users to build AI experiences rapidly while maintaining reusable architecture, governance, and operational controls




• Collaborate across engineering, architecture, data/analytics, security, QA, SRE/DevOps, Product Management, and customer-facing teams




• Define metrics for AI quality, task completion, containment/automation, latency, reliability, cost, adoption, customer outcomes, and engineering delivery performance




• Develop engineering managers and senior technical leaders




• Stay current with advances in generative AI, LLMs, agentic systems, evaluation methods, and AI infrastructure, making pragmatic build/buy/partner decisions

Requirements

• 10+ years of software engineering experience, including significant engineering leadership experience managing managers and/or multiple software development teams




• Proven ability to define and execute technical roadmaps for scalable, highly available cloud software products and platforms




• Strong understanding of software architecture, APIs, distributed systems, cloud-native development, security, observability, and modern software development life cycle practices




• Experience partnering with Product Management to translate business strategy and product roadmaps into executable engineering plans, estimates, milestones, and technical investments




• Experience building high-performing engineering organizations through hiring, coaching, performance management, succession planning, and development of engineering leaders and senior technical talent




• Strong knowledge of Agile development, CI/CD, automated testing, code quality, release management, and DevOps/SRE practices




• Strong problem-solving and analytical skills




• Excellent communication and leadership skills




• Experience with production generative AI applications, LLM platforms, AI assistants, conversational AI, or agentic systems




• Experience with agent orchestration, tool/function calling, RAG, embeddings/vector search, knowledge retrieval, prompt/configuration management, and model APIs




• Experience with AI evaluation, observability, guardrails, content/safety controls, latency optimization, token/model cost management, and production monitoring




• Cloud-native software development on Microsoft Azure and/or AWS




• Integration of AI with enterprise applications, APIs, communications/contact center systems, voice, messaging, or workflow automation strongly preferred




• Speech AI experience highly desirable




• Understanding of enterprise AI security, privacy, data governance, model governance, and responsible AI practices

Core Competencies

Demonstrates expertise in leading engineering organizations focused on AI applications, with a strong emphasis on architecture, technical roadmaps, and scalable cloud software development. Proficient in integrating AI technologies with enterprise systems while ensuring security, governance, and performance metrics.

Highest-signal resume keywords

• AI Application Development




• Cloud-Native Development




• Engineering Leadership




• Agile Development Practices




• Generative AI Experience

ATS Optimization Keywords

Hard Skills

• Software Architecture




• APIs




• Distributed Systems




• CI/CD




• Automated Testing




• DevOps Practices




• LLM Integration




• Agent Orchestration




• Prompt Management




• Model APIs

Soft Skills

• Excellent Communication




• Leadership Skills




• Problem-Solving




• Analytical Skills

Industry Keywords

• AI Security




• Data Governance




• Responsible AI Practices




• Observability




• Performance Management

Tools & Technologies

• Microsoft Azure




• AWS




• AI Assistants




• Conversational AI




• Speech AI