| Job Detail | Full Information |
|---|
| Job Title | Director – AI Engineer |
| Job Identification | 30043884 |
| Job Category | Partner / Director |
| Job Location | One, Bangalore, Karnataka – 560103, India |
| Posting Date | 22 October 2026 |
| Apply Before | 30 October 2026 |
| Job Type | Full-time |
| Experience Required | 15+ years in software engineering, data engineering, and AI/ML engineering, including 5+ years in senior technology leadership roles |
| Educational Qualification | Graduation |
| Role Overview | Lead AI Engineering teams and drive enterprise AI, Generative AI (GenAI), machine learning, intelligent automation, and agentic AI solutions. Define the AI engineering strategy and deliver scalable, secure, production-ready AI platforms. |
| Key Responsibilities | Define AI engineering vision, roadmap, and operating model; oversee GenAI platforms, AI-powered coding assistants, and agentic automation; drive AI modernization and enterprise deployment. |
| AI & GenAI Expertise | LLMs, GenAI architectures, agent-based systems, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, embeddings, context management, and AI workflow orchestration. |
| Technical Skills | Python, APIs, cloud-native AI platforms, and modern engineering stacks. Working knowledge of Java, Scala, or Go is preferred. |
| Cloud Platforms | Google Cloud Platform (GCP), AWS, Azure, and managed AI services. Preferred exposure to Gemini, OpenAI, Azure OpenAI, Vertex AI, and Amazon Bedrock. |
| MLOps / LLMOps | CI/CD for AI, model lifecycle management, evaluation, monitoring, observability, deployment, and AI cost governance. |
| AI Governance & Security | Responsible AI, AI governance, model risk management, explainability, auditability, security, privacy, and regulatory compliance. |
| Leadership Responsibilities | Lead large, distributed, multidisciplinary teams; hire and mentor talent; develop future leaders; establish OKRs, KPIs, and performance metrics; engage with senior executives and clients. |
| Cross-Functional Collaboration | Partner with Data Engineering, Cloud Engineering, Product, Security, Legal, and Risk teams to deliver enterprise AI solutions. |
| Preferred Skills | AI coding assistants, developer copilots, AI-driven software modernization, data mesh, federated AI/data architectures, and AI token optimization. |
| Preferred Industry Experience | Healthcare, Life Sciences, and Banking, Financial Services & Insurance (BFSI), particularly regulated environments. |
