- Agentic AI & GenAI Solution Leadership Solution Architecture - Own end-to-end AI solution architectures for Finance Ops and ERP AMS processes, from use-case shaping through production.

- Agentic Design - Direct the design of LLM and agentic workflows using LangChain, AutoGen, CrewAI, and Semantic Kernel - planning, tool use, memory, and human-in-the-loop controls.

- RAG & Retrieval - Govern RAG pipelines and embedding design using vector stores such as Pinecone, Chroma, or FAISS to deliver contextual, grounded intelligence.

- Prompt & Agent Standards - Set standards for prompt chains and autonomous-agent behavior, ensuring accuracy, governance, and auditability.

- ERP & Finance Integration Integration - Oversee integration of AI solutions with Oracle, SAP, and Finance Ops systems via APIs and OIC.

- AMS Automation - Direct automation of ticket triage, reporting, and communication drafts for AMS teams to reduce manual effort and improve speed and accuracy.

- Domain Alignment - Bring working knowledge of Finance data models and ERP processes to ground solution design in domain reality.

- Team Leadership & Delivery People Leadership - Lead, mentor, and grow a team of AI Solution Leads and Agentic AI / Automation Engineers - setting clear goals, KPIs, and career-development plans.

- Delivery Management - Run delivery in short (6-week) sprints, taking solutions from prototype to production while managing timelines, risks, quality, and client SLAs.

- Coaching - Coach the team on emerging GenAI and agentic techniques; foster a culture of rapid prototyping, experimentation, and continuous learning.

- Cross-Functional Lead - Lead cross-functional AI projects from POC to production, balancing hands-on technical input with delivery oversight.

- MS AI Factory & Reusability Reusable Assets - Define reusability frameworks and common components for the MS AI Factory to accelerate delivery across engagements.

- Capability Building - Contribute accelerators, patterns, and best practices to shared repositories and centers of excellence, and help win and shape new client engagements.

- LLMOps, Governance & Responsible AI LLMOps - Stand up LLMOps for GenAI and agentic workloads - versioning, prompt/agent management, and monitoring for drift, hallucination, latency, and cost.

- Governance & Responsible AI - Embed governance, auditability, guardrails, and Responsible AI (fairness, transparency, security, privacy) into every deployment, aligned to frameworks such as NIST AI RMF and applicable regulations.

- Cloud, CI/CD & Platform Cloud AI - Deliver solutions on cloud AI services - Azure OpenAI, AWS Bedrock, and GCP Vertex - optimized for scale, security, and cost.

- CI/CD - Oversee CI/CD automation with GitHub Actions, Docker, and Kubernetes for reliable, repeatable deployment.

- Automation Tooling - Apply enterprise automation tools ( UiPath, Power Automate, n8n) where they complement agentic solutions.

- Stakeholder Engagement & Advisory Collaboration - Collaborate with Finance and ERP SMEs to convert business cases into technical designs and measurable outcomes.

- Advisory - Act as a trusted advisor, presenting AI-driven insights and trade-offs to senior stakeholders in clear, non-technical language.

Required Skills & Experience :

- 9-15 years in AI/ML and automation, including 3-4+ years leading AI engineering teams with proven mentoring and delivery leadership.

- Advanced Python with LLM frameworks - LangChain, CrewAI, AutoGen, Semantic Kernel - and hands-on agentic solution building.

- Strong experience with LLM APIs (OpenAI, Anthropic, Gemini, Mistral), RAG patterns, vector databases (Pinecone, Chroma, FAISS), embeddings, and LLM fine-tuning.

- Experience integrating AI with ERP (Oracle / SAP) and Finance Ops systems via APIs and OIC, with familiarity with Finance data models.

- Proven delivery of AI solutions in Managed Services or ERP operations, leading cross-functional projects from POC to production.

- Cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex) and CI/CD automation (GitHub Actions, Docker, Kubernetes).

- LLMOps / MLOps for model, prompt, and agent lifecycle - monitoring, governance, and auditability.

- Excellent stakeholder engagement and executive communication, translating AI capability into business value.

Preferred / Nice-to-Have Skills :

- Experience delivering GenAI applications for enterprise Finance / ERP operations at scale.

- Exposure to ITSM, AMS, or Finance Managed Services environments and operating models.

- Familiarity with enterprise automation platforms (UiPath, Power Automate, n8n).

- LLMOps observability tooling (LangSmith, Langfuse, Arize) and evaluation frameworks for GenAI and agents.

- AI/ML or cloud certifications (Azure / AWS / GCP).

Why This Role Stands Out :

- Lead the agentic-AI transformation of Finance & ERP Managed Services - a rare blend of solution architecture, hands-on engineering, and team leadership.

- Build and grow a GenAI engineering team and shape the reusable AI Factory that scales across engagements.

- High-visibility role with direct client and senior leadership interaction across industries

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