Director of Engineering

Role Overview: At Intellectyx, as the Director of Engineering, you will be responsible for leading the architecture, development, and scaling of the digital and AI-native product ecosystem. Your role will involve aligning technical excellence with strategic vision to drive innovation, operational excellence, and delivery efficiency across distributed teams. Key Responsibilities: - Define and implement the engineering strategy and roadmap across digital, AI, and data domains. - Translate product vision into scalable, modular, and secure architectures. - Lead, mentor, and scale globally distributed engineering teams. - Foster a culture of engineering excellence, innovation, and accountability. - Partner cross-functionally with Product, Data Science, and Architecture teams for continuous innovation. - Ensure adherence to compliance, security, and quality standards. Core Focus Areas: 1. Digital Engineering - Lead end-to-end product and platform development using Python (Django, FastAPI), React, Redux, and PostgreSQL. - Architect modular APIs and microservices focused on scalability, performance, and reliability. - Oversee CI/CD, observability, and infrastructure automation within AWS and Azure environments. 2. Agentic AI Frameworks - Drive adoption and engineering excellence using AgnoAI, MCP, LangChain, LangGraph, and Langfuse. - Build and orchestrate multi-agent systems, integrating LLM-based reasoning and autonomous task execution. - Establish engineering patterns for AI-native architectures leveraging Python 3.13, FastAPI, and PostgreSQL 16. 3. Data & Analytics - Oversee architecture and engineering of data platforms using Snowflake, Azure Synapse, Azure Data Factory, and Databricks. - Integrate Tableau and Power BI for self-service analytics, visual storytelling, and executive dashboards. - Ensure data observability, lineage, and quality frameworks are embedded across pipelines. - Partner with AI and Product teams to deliver governed, scalable, and intelligent data ecosystems. 4. Cloud Infrastructure - Lead multi-cloud deployments in AWS and Azure, ensuring reliability, cost efficiency, and resilience. - Champion Infrastructure-as-Code (Terraform) and container orchestration (Kubernetes). - Drive unified observability, monitoring, and incident management across hybrid environments. Qualifications: - 12+ years in software engineering, with 5+ years in senior technical leadership. - Proven experience delivering complex SaaS, AI, or data platform solutions. - Strong technical expertise in digital, Agentic AI, Data & Analytics, and Cloud technologies. - Strong grasp of architecture, scalability, security, and reliability principles. - Excellent leadership, communication, and stakeholder management skills. Preferred Experience: - Experience delivering AI-native or multi-agent products in production. - Familiarity with data quality, observability, and governance frameworks. - Experience leading distributed engineering organizations across geographies. - Contributions to open-source or research in digital, data, or AI engineering. Note: Additional details about the company were not provided in the job description.,