Lead - AI/ML Engineer (Generative AI Agent Systems)

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead - AI/ML Engineer (Generative AI Agent Systems) based in India.** As a Lead AI/ML Engineer specializing in Generative AI Agent Systems, you will drive the design and delivery of next-generation AI solutions that address complex enterprise challenges. This strategic and highly visible role combines technical leadership, client advisory responsibilities, and hands-on architecture development across advanced AI ecosystems. You will work at the forefront of autonomous agents, large language models, and cloud-native AI technologies, helping organizations transform ambitious AI initiatives into scalable and secure business outcomes. The position offers the opportunity to collaborate with senior stakeholders, influence enterprise AI strategies, and establish reusable frameworks that shape future consulting engagements. This role is ideal for an experienced AI leader who thrives in innovation-driven environments and enjoys solving high-impact technical challenges. ### Accountabilities: - Serve as the primary subject matter expert for Generative AI, large language models, reasoning frameworks, and autonomous agent ecosystems across enterprise engagements. - Lead technical discovery sessions and collaborate with senior client stakeholders to translate business requirements into scalable AI architectures and implementation roadmaps. - Define and establish reusable delivery frameworks, playbooks, and best practices for deploying agentic AI solutions across multiple industries and use cases. - Design and own the technical vision for production-ready agent architectures, leveraging modern AI development frameworks and cloud-native technologies. - Lead the specification and implementation of AI agents, including function calling frameworks, prompt engineering methodologies, context management, and data interaction patterns. - Define autonomy models and human-in-the-loop (HITL) strategies to ensure appropriate governance, oversight, and operational reliability. - Establish distributed systems principles, including event-driven architectures, idempotent processing strategies, and scalable integration patterns. - Design and oversee continuous evaluation frameworks, shadow-mode testing environments, and validation processes to ensure safe and reliable AI deployments. - Define performance metrics, safety thresholds, and model evaluation methodologies to support production readiness and ongoing optimization. - Advise stakeholders on AI governance, model lifecycle management, version control, compliance requirements, and drift monitoring strategies. - Lead proof-of-concept initiatives and accelerate the adoption of enterprise-grade AI agent solutions through hands-on technical leadership and mentorship. ## Requirements - Extensive experience in AI/ML engineering, with significant expertise in Generative AI, large language models, autonomous agents, and multi-agent systems. - Proven background in professional services, consulting, or client-facing technology leadership roles, with experience engaging senior stakeholders such as CTOs and enterprise architects. - Deep hands-on experience designing and deploying production-grade AI agent systems, reasoning frameworks, and LLM-powered workflows. - Expert-level knowledge of the Google Cloud ecosystem, particularly Vertex AI services, including Agent Development Kit (ADK), Agent Engine, Vector Search, model tuning, and related AI capabilities. - Strong expertise in enterprise cloud security architectures, including identity management, network security, and secure AI deployment frameworks. - Advanced software engineering capabilities with strong proficiency in Go (Golang) and extensive experience building distributed, highly concurrent, and event-driven systems. - Solid understanding of AI governance, model evaluation methodologies, observability, monitoring, and respons…