Ai agentic engineer

# Principal AI Architect / Senior AI Engineering Lead ## Role Overview We are seeking an experienced Principal AI Architect to lead the design, development, and deployment of enterprise-scale generative AI and agentic systems. This role combines strategic AI leadership with hands-on technical expertise, driving the adoption of advanced AI solutions that deliver measurable business impact across sales, marketing, knowledge management, and business operations. The ideal candidate will have deep experience with large language models (LLMs), agent orchestration frameworks, retrieval-augmented generation (RAG), cloud-native architectures, and production AI systems. They will be responsible for defining AI architecture standards, leading cross-functional delivery teams, and translating business challenges into scalable AI-powered solutions. ## Key Responsibilities ### AI Architecture & Strategy * Define and execute the enterprise AI architecture roadmap, aligning AI initiatives with business objectives. * Design scalable, secure, and production-ready generative AI and agentic system architectures. * Establish best practices for AI governance, observability, evaluation, and deployment. * Drive innovation through the adoption of emerging AI technologies, frameworks, and methodologies. ### Agentic Systems & Generative AI Solutions * Architect and deliver multi-agent systems using modern orchestration frameworks such as LangGraph, LangChain, Google ADK, or equivalent technologies. * Design and implement retrieval-augmented generation (RAG) architectures integrating structured and unstructured enterprise data sources. * Develop autonomous workflows for knowledge management, document processing, content generation, decision support, and business automation. * Build intelligent assistants and AI-powered applications integrated with enterprise collaboration and productivity platforms. ### AI Product Development * Lead end-to-end delivery of AI products from concept, prototyping, and MVP development through to production deployment. * Design AI-powered solutions for sales automation, customer engagement, proposal generation, marketing optimization, and operational efficiency. * Evaluate and select appropriate models, architectures, and infrastructure to meet business and technical requirements. * Ensure AI systems are scalable, maintainable, and aligned with enterprise security and compliance standards. ### Data & Platform Engineering * Design automated data ingestion, enrichment, embedding, and indexing pipelines. * Implement vector database and semantic search architectures to support enterprise AI use cases. * Build cloud-native AI platforms leveraging modern infrastructure and MLOps practices. * Establish monitoring, evaluation, and continuous improvement frameworks for AI applications. ### Leadership & Stakeholder Management * Partner with product, engineering, sales, marketing, and executive stakeholders to identify and prioritize AI opportunities. * Provide technical leadership and mentorship to AI engineers, software engineers, and data practitioners. * Communicate AI strategy, architecture decisions, and business value to both technical and non-technical audiences. * Lead cross-functional teams to deliver high-impact AI initiatives on time and at scale. ## Required Qualifications * 8+ years of experience in software engineering, machine learning, data engineering, or AI solution architecture. * 3+ years of experience designing and deploying production-grade generative AI applications. * Strong expertise in large language models (LLMs), prompt engineering, agentic systems, and retrieval-augmented generation (RAG). * Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, Google ADK, AutoGen, CrewAI, or similar. * Experience with vector databases, semantic search, embeddings, and enterprise knowledge systems. * Strong cloud architecture experience with platforms such as Google Cloud Platform (GCP), AWS, or Azure. * Proficiency in Python and modern software engineering practices. * Experience integrating AI solutions with enterprise systems such as CRM, collaboration, content management, and workflow platforms. * Proven ability to lead complex technical initiatives from concept to production. ## Preferred Qualifications * Experience building multi-agent systems and autonomous business workflows. * Expertise in enterprise AI governance, evaluation, and responsible AI practices. * Experience with MLOps, DevOps, CI/CD, and cloud-native deployment patterns. * Track record of rapidly delivering AI MVPs and scaling them into production solutions. * Experience leading technical teams and influencing executive-level stakeholders. ## Key Technologies * Large Language Models (OpenAI, Gemini, Anthropic, or equivalent) * LangGraph, LangChain, Google ADK * Python * PostgreSQL, Vector Databases * Retrieval-Augmented Generation (RAG) * Google Cloud Platform (GCP) * Slack API, Notion API, Salesforce Integrations * Streamlit * Agentic AI Frameworks * MLOps & Cloud Infrastructure ## Success Measures * Delivery of scalable, production-ready AI solutions that generate measurable business value. * Increased automation, operational efficiency, and decision-making effectiveness across business functions. * Establishment of enterprise AI architecture standards and best practices. * Successful adoption of AI solutions by business stakeholders and end users.