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

• Help customers to realise the value of AI and drive adoption of Red Hat AI technology • Develop new consulting solutions that address common customer use cases • Support our sales teams in positioning Red Hat AI Consulting solutions to customers • Act as lead architect on cutting-edge AI consulting projects for our customers

Role Description As an AI Engineer, you will play a key role in designing, developing, and deploying enterprise-grade Azure AI solutions that enable scalable conversational AI, intelligent automation, and advanced analytics across scientific and business workflows. You will combine hands-on engineering with solution design, integrating large language models, vector search technologies, data pipelines, and cloud services into secure, reliable, and governed platforms. Working closely with data scientists, product managers, engineers, and business stakeholders, you will translate complex requirements into practical AI capabilities that deliver measurable business value. You will help drive innovation through intelligent systems while ensuring that solutions are scalable, maintainable, compliant, and aligned with organisational architecture and governance standards. This is an exciting opportunity for an AI professional who is passionate about emerging technologies, enjoys solving complex problems, and wants to help shape the future of AI-enabled products and services. What you'll be doing: - Design and implement end-to-end AI solutions using Azure AI Foundry, Azure Machine Learning, and Cognitive Services to support innovative business and scientific applications - Develop, fine-tune, and deploy Large Language Model (LLM)-powered chatbots and autonomous AI agents that enhance user experiences and business processes - Define, maintain, and optimise AI models, data flows, and integration patterns across enterprise platforms - Collaborate with data scientists, data engineers, product managers, and business stakeholders to translate requirements into scalable technical solutions - Integrate AI services, vector databases, embeddings, and cloud-native technologies into secure and resilient architectures - Ensure AI solutions comply with governance standards, metadata management practices, and traceability requirements - Contribute to the continuous improvement of AI platforms, frameworks, and engineering practices to drive innovation and operational excellence - Support the adoption of AI technologies across the business by providing technical expertise and guidance to stakeholders and colleagues Qualifications - Bachelor's degree in Computer Science, Information Technology, or a related discipline, or equivalent practical experience - Typically 2+ years of experience in AI Engineering, Machine Learning Engineering, or a similar industry role - Strong experience designing and deploying Azure AI solutions in enterprise environments - Hands-on experience with Large Language Models (LLMs), vector databases, embeddings, conversational AI, and autonomous agent development - Proficiency in Python, PowerShell, SQL, JSON, and integrating AI services with wider business applications - Understanding of AI governance, metadata management, traceability, and responsible AI practices - Strong analytical and problem-solving skills with the ability to design practical solutions for complex challenges - Excellent communication and stakeholder engagement skills, with experience collaborating across multidisciplinary teams - Azure AI certifications are desirable - Experience in scientific, research, or technology-driven environments would be advantageous Benefits - Join an ambitious, growing international organisation where innovation and technology are central to our success - Play a key role in shaping the future of AI solutions that create value for customers and the business - Collaborate with global teams of engineers, scientists, and technology specialists working on cutting-edge projects - Benefit from ongoing learning opportunities and professional development in one of the fastest-growing technology domains - Enjoy a comprehensive and competitive rewards package designed to support your wellbeing, growth, and success

• Build agentic workflows and AI-powered products. • Design and deliver production-grade AI solutions from concept to deployment. • Collaborate closely with Product and Engineering teams to deliver high-quality software. • Take ownership of ambiguous problems and drive initiatives end-to-end. • Mentor engineers and help elevate the team's AI capabilities. • Contribute to the evolution of AI standards, patterns, and engineering practices. • Develop scalable and maintainable solutions in a polyglot environment. • Promote strong collaboration and transparent communication across teams. • Influence the technical direction and AI culture of the organization.