• Lead the design and development of production AI systems powering insurance workflow automation. • Architect AI orchestration layers connecting LLMs, backend services, and business workflows. • Own end-to-end AI system design, including inference pipelines, routing, caching, and fallback strategies. • Drive engineering decisions around latency, reliability, cost, and scalability of AI services. • Lead implementation of Observability Systems (logging, monitoring, tracing, alerting). • Review and guide backend AI implementation across engineering teams. • Collaborate with product, backend, DevOps, and operations teams to ship end-to-end AI features. • Debug complex production issues across distributed AI systems and lead root-cause analysis. • Define engineering standards and best practices for AI system development. • Mentor engineers and elevate technical execution quality across teams.

• Lead the design and development of production AI systems powering insurance workflow automation. • Architect AI orchestration layers connecting LLMs, backend services, and business workflows. • Own end-to-end AI system design, including inference pipelines, routing, caching, and fallback strategies. • Drive engineering decisions around latency, reliability, cost, and scalability of AI services. • Lead implementation of Observability Systems (logging, monitoring, tracing, alerting). • Review and guide backend AI implementation across engineering teams. • Collaborate with product, backend, DevOps, and operations teams to ship end-to-end AI features. • Debug complex production issues across distributed AI systems and lead root-cause analysis. • Define engineering standards and best practices for AI system development. • Mentor engineers and elevate technical execution quality across teams.

• Architect end-to-end AI/ML solutions • Define and implement model lifecycle controls • Design secure integration patterns across AWS, Azure, Salesforce, and Azure DevOps • Establish governance aligned to RMF constraints • Define model evaluation frameworks and implement monitoring for model performance • Oversee CI/CD integration for model deployment • Lead root-cause analysis and triage automation architecture • Mentor engineers and direct technical execution

Role Description We have got a contract opportunity for AI Lead / Lead GenAI Engineer (SAP FICO Functional Background) with one of our clients. The detail of the position is as given below. - Job Title: AI Lead / Lead GenAI Engineer (SAP FICO Functional Background) - Location: Torrance, CA (Remote) - Duration: 6+ Months We are looking for an AI Lead / GenAI Engineer with strong SAP FICO functional expertise to drive AI-powered solutions across finance processes. The role focuses on leveraging Generative AI, LLMs, and automation to optimize SAP FICO operations. Key Responsibilities: - Analyze SAP FICO processes (GL, AP, AR, CO) and identify AI use cases - Design and implement GenAI solutions (LLMs, Prompt Engineering, RAG) - Develop and implement RAG-based solutions using enterprise financial and SAP data - Lead POC development and scale solutions into production environments - Build POCs and scale to production environments - Collaborate with finance stakeholders to translate business requirements into AI-driven workflows and automation strategies - Drive automation in finance processes like reconciliation, reporting, and validation - Integrate AI solutions with SAP (S/4HANA/ECC) using APIs/OData/BTP Qualifications - Strong SAP FICO functional experience (S/4HANA/ECC) - Hands-on exposure to GenAI / LLMs / AI automation - Experience with cloud platforms (AWS/Azure) - Ability to bridge business (finance) and AI solutions