Director - AI Engineer

Job Requirements Mandatory Skills 15+ years of experience across software engineering, data engineering, and AI/ML engineering, with 5+ years in senior technology leadership roles Strong engineering foundation with hands‑on experience as an individual contributor before transitioning into leadership Proven experience building and scaling enterprise AI platforms , including GenAI, ML, and intelligent automation solutions Expertise in LLMs, GenAI architectures, agent-based systems, and AI workflow orchestration Hands-on understanding of prompt engineering, RAG architectures, vector databases, embeddings, and context management Experience implementing AI solutions on cloud-native platforms (GCP, AWS, Azure) , including managed AI services Strong proficiency in Python , APIs, and modern engineering stacks; working knowledge of Java/Scala/Go preferred Deep understanding of MLOps / LLMOps , CI/CD for AI, model lifecycle management, and observability Experience with Responsible AI, AI governance, security, privacy, and compliance , especially in regulated environments Proven ability to lead large, distributed, multi-disciplinary teams and drive organizational change Strong stakeholder management skills and ability to engage with senior leadership and client executives Primary Roles and Responsibilities Provide strategic and operational leadership for AI Engineering teams delivering enterprise AI, GenAI, and agentic solutions Define and execute the AI engineering vision, roadmap, and operating model aligned with business strategy Oversee the design and delivery of: GenAI platforms and reusable AI capabilities AI-powered developer productivity and coding assistant solutions Agentic and workflow-driven automation systems Ensure scalable, secure, and governed AI architectures , including RAG, orchestration layers, and enterprise context management Partner closely with Data Engineering, Cloud Engineering, Product, Security, Legal, and Risk teams Drive adoption of MLOps / LLMOps best practices , including CI/CD, evaluation, monitoring, and cost governance Establish AI governance frameworks covering responsible AI, model risk, explainability, auditability, and regulatory compliance Promote a platform and product mindset , enabling reuse, standardization, and accelerated delivery Lead AI modernization initiatives , including migration from experimental AI to production-grade enterprise deployments Build and scale high‑performing teams through hiring, mentoring, and leadership development Define clear OKRs, KPIs, and success metrics for AI engineering initiatives Represent the AI Engineering function in enterprise forums, client engagements, and innovation councils Drive collaboration, transparency, and a culture of continuous learning and innovation Preferred Skills Experience with enterprise GenAI platforms (Gemini, OpenAI, Azure OpenAI, Vertex AI, Bedrock, etc.)

Exposure to AI coding assistants, developer copilots, and software modernization using AI Knowledge of data mesh or federated AI/data architectures Experience working with regulated industries (Healthcare, Life Sciences, BFSI) Strong understanding of AI cost management, token optimization, and usage governance Demonstrated ability to influence at executive and board levels