Agentic AI & Automation Lead - Manager

Overview

This role is focused on leading agentic AI and generative AI initiatives specifically for Finance Operations and ERP Application Management Services (AMS). The position demands ownership from solution architecture through to deployment, utilizing advanced AI frameworks and integrations with ERP systems like Oracle and SAP.

Key Responsibilities

• Design end-to-end AI solutions tailored to finance and ERP AMS processes.
• Lead the creation of Large Language Model (LLM) and agentic workflows using tools such as LangChain, AutoGen, CrewAI, and Semantic Kernel, incorporating memory and human-in-the-loop mechanisms.
• Govern design and implementation of Retrieval Augmented Generation (RAG) pipelines leveraging vector databases like Pinecone, Chroma, or FAISS to ensure contextual, precise intelligence delivery.
• Establish standards for prompt chains and autonomous agent operations focusing on accuracy, governance, and audit capabilities.
• Manage integration of AI applications with ERP and Finance systems using APIs and Oracle Integration Cloud (OIC).
• Drive automation of ticket processing, reporting, and communication drafts within AMS to enhance efficiency and accuracy.
• Apply domain expertise in Finance data models and ERP processes to guide solution relevance.
• Lead and mentor a team of AI Solution Leads and Automation Engineers, setting performance indicators and growth paths.
• Oversee project delivery via short iterative sprints, managing risks, timing, quality, and service level agreements with clients.
• Provide continuous coaching on emerging generative and agentic AI methods, encouraging rapid experimentation and learning.
• Coordinate cross-functional AI projects from proof-of-concept to production stage.
• Develop reusability frameworks and common components for AI delivery acceleration.
• Contribute to capability building through patterns, accelerators, best practices, and aid in client engagement development.
• Implement LLMOps strategies including version control, prompt/agent lifecycle management, and monitoring for issues like model drift and hallucinations.
• Embed governance, responsible AI principles, and compliance with frameworks such as NIST AI RMF into deployments.
• Deploy AI solutions utilizing cloud services (Azure OpenAI, AWS Bedrock, GCP Vertex) with scalability, security, and cost optimization.
• Manage continuous integration and deployment automation using GitHub Actions, Docker, and Kubernetes.
• Incorporate enterprise automation tools like UiPath, Power Automate, and n8n where applicable.
• Collaborate with finance and ERP domain experts to translate business requirements into actionable AI solutions.
• Act as a trusted consultant presenting AI benefits and trade-offs to senior stakeholders in accessible language.

Required Qualifications and Experience

• 9 to 14 years of experience in AI, machine learning, and automation, including at least 3 to 4 years in leadership roles managing AI engineering teams with proven delivery track records.
• Proficiency in advanced Python programming and deep experience with LLM frameworks such as LangChain, CrewAI, AutoGen, and Semantic Kernel.
• Hands-on expertise with LLM APIs (e.g., OpenAI, Anthropic, Gemini, Mistral), RAG mechanisms, vector databases (Pinecone, Chroma, FAISS), embeddings, and model fine-tuning.
• Experience integrating AI solutions with major ERP platforms (Oracle, SAP) and Finance Operations systems through APIs and OIC, with a solid understanding of finance data architectures.
• Track record of delivering AI projects in Managed Services or ERP operations, leading multidisciplinary teams from concept to production.
• Familiarity with cloud-based AI services including Azure OpenAI, AWS Bedrock, and GCP Vertex and with CI/CD pipelines via GitHub Actions, Docker, and Kubernetes.
• Expertise in LLMOps or MLOps practices for managing AI lifecycle governance, monitoring, and auditability.
• Strong skills in stakeholder engagement and clear communication of AI solutions' business implications to senior executives.

Preferred Additional Skills

• Experience deploying GenAI applications at enterprise scale in Finance or ERP operations.
• Knowledge of ITSM, AMS, or Finance Managed Services processes and frameworks.
• Familiarity with enterprise automation platforms such as UiPath, Power Automate, or n8n.
• Experience with observability and evaluation tools for LLMOps (LangSmith, Langfuse, Arize) and frameworks specifically for GenAI and agent management.
• Professional certifications in AI/ML or cloud platforms (Azure, AWS, GCP) are an advantage.

Additional Information

• This role provides the unique opportunity to lead the transformation of Finance & ERP Managed Services using agentic AI technology, combining architecture, engineering, and leadership.
• Responsibilities include developing and scaling a generative AI engineering team alongside shaping reusable AI assets for multiple engagements.
• This position entails close client and leadership collaboration across various industries with high visibility.