Director – AI Engineering, Platforms & Solutions
Designation: Director – Tech & AI
Location: India Preferred | Hybrid
Reports to: VP – Engineering
Role Overview
iQuanti is seeking a hands-on Director – AI Engineering, Platforms & Solutions to lead the firm’s AI-first, AI-native, and Agentic evolution. This role will own the strategy, architecture, engineering, deployment, and adoption of AI platforms, agent ecosystems, automation frameworks, AI-native products, and reusable solution IP across the organization.
This is an engineering-first leadership role focused on building AI at scale, while also modernizing and productizing iQuanti’s existing and future platforms such as ALPS, SIERA, LEAP, and other reusable IP assets. The leader will partner with business, product, delivery, and engineering teams to convert domain expertise into scalable AI-powered products, solutions, agents, copilots, accelerators, and workflows using full-stack engineering, microservices, APIs, AWS cloud, DevOps, and strong engineering governance.
Role Mission
Build the AI foundation that enables iQuanti to scale delivery without proportional headcount growth, improve productivity and margins, develop AI-powered service offerings, create reusable AI accelerators and intellectual property, automate internal business processes, and establish enterprise AI capabilities that create long-term competitive advantage.
1. AI Engineering, Platforms & Agent Ecosystem – 40%
Own the architecture, engineering, deployment, and scalability of enterprise AI platforms, agent frameworks, multi-agent systems, RAG architectures, knowledge management platforms, AI orchestration layers, and shared AI services. Lead the development of AI agents, autonomous workflows, copilots, decision-support systems, and process automation solutions. Establish engineering standards for AI application development, prompt engineering, model evaluation, security, compliance, monitoring, and production deployment. Drive AI engineering through cloud-native architecture, API-first design, microservices, DevOps, CI/CD, and strong engineering governance.
2. Product & Solution Engineering Leadership – 40%
Lead the architecture, engineering, modernization, and scale of iQuanti’s AI-native products, platforms, accelerators, and reusable solution IP. Own the engineering direction for existing and future product/solution assets such as ALPS, SIERA, LEAP, and other internal or client-facing platforms. Drive scalable SaaS-style product development using full-stack engineering, Python, ReactJS, microservices, APIs, AWS cloud, databases, integrations, DevOps, and CI/CD. Partner with Product Owners, Engineering, Delivery, and business leaders to define product roadmaps, technical backlog, architecture choices, and delivery priorities. Embed AI and Agentic capabilities into existing products and solutions to improve automation, intelligence, productivity, quality, and client impact. Convert internal innovations and service-line needs into reusable platforms, accelerators, demos, and commercialise solution IP.
3. Enterprise AI Transformation & Adoption – 20%
Define and execute the enterprise AI roadmap while establishing governance, security, compliance, and responsible AI practices. Build an AI Champions network, develop training programs and adoption frameworks, and drive enterprise-wide use of approved AI platforms. Lead AI transformation initiatives across Delivery, Growth, HR, Finance, Recruiting, Operations, Marketing, and Technology, with a focus on measurable productivity, quality, margin, and business impact. Partner with business leaders to challenge existing workflows and identify what should be automated, augmented, or fundamentally reimagined through AI.
Organization Structure
The role will lead a centralized AI Engineering and Enablement organization comprising AI Engineers, AI Architects, Agent Developers, Platform Engineers, Full-Stack Engineers, Automation Specialists, and AI Product Managers. The team will support all business units and service lines.
Budget Ownership
Own AI platform investments, AI tooling and licensing strategy, external technology partnerships, engineering staffing plans, and AI innovation budgets. Partner with business and finance leaders to prioritize investments and maximize ROI.
Decision Rights
Own enterprise AI architecture standards, platform selection, AI governance frameworks, agent development standards, engineering priorities, deployment practices, product architecture standards, and AI platform roadmap decisions. Influence AI solution prioritization, product roadmap decisions, and reusable IP investments across business functions and service lines.
Leadership Expectations
Provide strategic leadership for iQuanti’s AI vision while remaining deeply involved in architecture, engineering, and innovation. Build and mentor a high-performing AI engineering organization, foster a culture of experimentation and accountability, and develop future AI leaders. Partner effectively with business leaders to convert domain expertise into scalable AI-powered capabilities.
Required Qualifications
15+ years of technology, software engineering, AI, product development, or digital transformation experience, including significant experience leading engineering organizations and enterprise-scale initiatives. Proven experience building and scaling AI-enabled platforms, products, agents, automation solutions, or reusable technology IP. Strong experience managing cross-functional engineering teams and working with senior business, product, delivery, and technology stakeholders.
Technical Expertise
Deep expertise in Generative AI, Large Language Models, Agentic AI, multi-agent systems, RAG architectures, prompt engineering, vector databases, AI governance, model evaluation, and enterprise AI deployment. Hands-on experience or strong working knowledge of technologies such as OpenAI, Claude, Gemini, Azure OpenAI, AWS AI services, LangGraph, CrewAI, LangChain, LlamaIndex, Copilots. Strong engineering experience with Python, ReactJS, AWS cloud, full-stack development, APIs, integrations, microservices, SaaS platforms, databases, DevOps, and CI/CD.
Success Metrics – First 12 Months
Establish the enterprise AI platform and governance framework; deploy production-ready AI agents and copilots; launch reusable AI accelerators across service lines; achieve measurable adoption of AI tools and workflows; improve productivity and margins through automation; support AI-enabled client solutioning and revenue growth; and build a scalable AI engineering organization capable of supporting future expansion.
3-Year Vision / Charter
Establish iQuanti as an AI-enabled and AI-native services organization with reusable AI platforms, enterprise agent ecosystems, AI-powered delivery workflows, and differentiated client offerings. Launch scalable AI products and solutions that strengthen iQuanti’s market positioning, create reusable IP, and drive measurable improvements in productivity, quality, scalability, margin performance, client impact, and revenue growth through AI-driven innovation.
