Location: Remote / Hybrid Experience: Senior Level (7–10+ years) Contract: Immediate Requirement We are looking for a highly skilled Senior AI / LLM Lead to architect, optimize, and evaluate advanced Large Language Model (LLM) systems that power next-generation enterprise intelligence. If you thrive at the intersection of AI engineering, knowledge systems, and multi-agent orchestration, this role is for you. What You’ll Do LLM Architecture & Optimization Design enterprise-ready LLM-based reasoning frameworks Architect RAG pipelines combining structured & unstructured enterprise knowledge Fine-tune and optimize foundation models for diagnostics, troubleshooting & decision support Build scalable prompt orchestration frameworks (hierarchical, adaptive, tool-use prompts) Evaluate emerging LLM modalities — multimodal, reasoning-augmented, and tool-enabled models Knowledge Engineering Partner with SMEs to extract and embed expert knowledge Develop semantic embeddings , vector stores, and hybrid retrieval systems Build & maintain domain ontologies , entity graphs, and factual grounding systems Ensure model transparency using citation generation & provenance tracking Agentic AI & Multi-Model Integration Integrate LLMs into multi-agent architectures Define LLM–tool interaction schemas with Agentic AI teams Build adaptive memory using vector, relational & graph storage Performance, Safety & Evaluation Create evaluation pipelines for accuracy, grounding, coherence & bias Implement RLHF and continuous learning feedback loops Run A/B tests on prompts, architectures & retrieval strategies Ensure compliance with AI governance, privacy & ethical standards What You Bring Deep expertise in transformer architectures , fine-tuning & LLM optimization Strong experience with RAG systems , embedding models & retrieval frameworks Proficiency in Python, PyTorch , and distributed inference optimization Hands-on experience with multi-agent orchestration (AutoGen, Semantic Kernel, LangChain Agents) Strong understanding of prompt engineering, context management & token efficiency Experience building knowledge graphs , vector databases & retrieval APIs Strong analytical skills for LLM evaluation & experiment design Preferred Qualifications 7+ years in applied NLP, ML, or AI systems 2+ years working directly with LLM fine-tuning or enterprise RAG systems Graduate degree in CS, ML, Computational Linguistics or related fields Experience in industrial, engineering, or diagnostics domains (plus)
Location: Remote / Hybrid (as required) Experience: 10+ Years (Preferred) Type: Full-time / Contract We're looking for a highly skilled SAP Fieldglass Consultant with strong integration and procurement domain expertise. If you have deep experience implementing CLM and SPM modules, managing master data, and driving integrations with ERP/Ariba systems, we want to talk to you. Key Responsibilities Configure and support SAP Fieldglass modules , workflows, reporting tools, and integrations. Lead Contingent Labor Management (CLM) and Services Procurement Management (SPM) implementations. Set up timesheet, expense reporting, and invoicing functionalities end-to-end. Manage and troubleshoot master data integration with ERP, HRIS, and other enterprise systems. Independently resolve integration issues and ensure stable data flows. Develop and execute test scripts, test data, test conditions , and document test results. Provide reporting insights and support business decision-making. Partner with procurement, vendor management, and IT teams for requirement gathering and solution design. Required Skills Strong expertise in SAP Fieldglass (modules, workflows, integrations). Hands-on experience in CLM (Time & Material) and SPM (Statement of Work) . Experience integrating SAP Fieldglass with SAP ERP, SAP Ariba, HR, and Payroll systems. Master data mapping, validation, issue resolution, and integration troubleshooting skills. Strong analytical skills and ability to generate meaningful insights. Ability to work independently and handle complex integration challenges. Preferred Qualifications SAP Fieldglass certification (a plus). 10+ years of experience in SAP Fieldglass, Ariba, or related procurement systems. Prior experience in enterprise-scale procurement or contingent workforce programs.