Head of technology

ole Overview

You will serve as the technology compass for our platform—owning architecture, engineering velocity, product-tech alignment, and the entire AI/Agentic innovation pipeline. The role requires a builder’s instinct, an architect’s discipline, and a delivery leader’s calm confidence. You’ll lead engineering teams, shape platform roadmaps, and bring agentic AI concepts to life from first sketch to deployment.

Key Responsibilities

1. Technology Leadership & Vision

• Define and evolve GrowQR's long-term technology architecture, ensuring scalability, modularity, and low-latency agentic flows.
• Translate strategic business objectives into actionable engineering roadmaps.
• Build and mentor high-performing engineering pods (AI, backend, frontend, DevOps, data, QA).
• Establish engineering best practices—CI/CD, secure coding, sprint velocity tracking, delivery governance.

2. Agentic AI & ML Ownership

• Lead design and development of advanced Agentic AI systems, multi-agent orchestration, LLM workflows, retrieval pipelines, and autonomous task frameworks.
• Architect full-stack AI layers—data ingestion, modeling, vector stores, RAG, evaluation, monitoring.
• Deliver production-grade AI/ML features with measurable performance benchmarks.
• Stay ahead of emerging AI ecosystems (OpenAI, Anthropic, Gemini, Llama, CrewAI, etc.).

3. End-to-End Delivery & Execution

• Own the entire lifecycle—from concept → storyboarding → low-fidelity flows → architecture → development → testing → deployment → optimization.
• Implement strong observability, logging, monitoring, and reliability frameworks.
• Manage technical risk, dependencies, and timelines for multi-team, multi-stream delivery.
• Drive cloud infrastructure strategy (Azure/GCP/AWS) with an emphasis on cost efficiency and robustness.

4. Product & Cross-Functional Collaboration

• Translate user personas and customer journeys into technical specifications.
• Support GTM, enterprise onboarding, and integrations with partners/clients.

5. Architecture & Platform Innovation

• Architect distributed systems with an emphasis on minimal hops, modular agents, and high throughput.
• Oversee API strategy, microservices, data pipelines, event-driven architecture, and governance.
• Build secure, compliant frameworks for identity, authentication, data privacy, and role-based access.

Required Qualifications

Experience & Technical Expertise

• 9-10 years of progressive, hands-on experience leading engineering teams and tech organizations.
• 5+ years of experience in applied Machine Learning, Deep Learning, NLP, or LLMs.
• At least 2 years of solid, demonstrable experience in Agentic AI—multi-agent systems, autonomous agents, or complex LLM workflows.
• Proven track record of delivering major revenue generation platform or applications for global clients or MNCs (enterprise scale preferred).
• Strong knowledge of modern tech stacks: Python, Node.js/TypeScript, FastAPI, LangChain, CrewAI, vector DBs, event buses, microservices, API gateways.
• Deep grounding in cloud-native engineering: Kubernetes, serverless, observability, infra-as-code.
• Experience with real-time systems, distributed architectures, and performance optimization.

Leadership & Execution Skills

• Ability to think from both 10,000 ft and 10 cm—vision + precision.
• Strong team building and people development orientation.
• Exceptional communication skills and an instinct for simplifying complexity.
• Proven ability to deliver under deadlines and lead through ambiguity.

Preferred Attributes

• Prior startup or zero-to-one product leadership experience.
• Familiarity with consumer and enterprise marketplaces, HR-Tech, Ed-Tech, or AI ecosystems.
• A natural storyteller—able to express architecture, logic, and product intent with clarity.
• Hunger for innovation; comfort with evolving landscapes and rapid prototyping.