• Install and configure laboratory software systems • Integrate software into laboratory workflows, including mapping daily processes • Deliver and implement Laboratory Information System (LIS) projects • Act as a subject matter expert within your field • Serve as a trusted technical contact for customers during projects and assignments • Support the adoption of emerging technologies, including data-driven and AI-enabled solutions • Identify opportunities to optimise laboratory workflows and system performance • Work with the Project Manager or Customer Services Manager and follow their guidance and planning. • Make proposals and identify technical risks, including those related to data integrity and AI-enabled functionalities, and communicate them clearly. • Prepare execution plans and relevant documentation. • Ensure all work is properly documented in internal systems (projects and aftersales). • Deliver assigned tasks according to project plan, budget, and quality standards. • Take full responsibility for all technical aspects of assigned tasks. • Keep stakeholders informed about progress and risks. • Demonstrate flexibility and support on-site customer implementations. • Manage and implement small projects or sub-projects. • Deliver customer training, including guidance on system data usage and reporting capabilities. • Act as interface between customer and development teams. • Organize and execute internal and external project handovers. • Perform update and upgrade projects

• Diseñar e implementar soluciones de observabilidad (logs, métricas y trazas) adaptadas a cada cliente, especialmente con ELK Stack. • Crear dashboards, alertas y visualizaciones avanzadas con Grafana. • Implementar instrumentación en apps y trazabilidad distribuida con OpenTelemetry. • Añadir capacidades de IA a las plataformas de Observabilidad. • Analizar problemas de rendimiento, disponibilidad y capacidad. • Colaborar con equipos de desarrollo DevOps y SRE para mejorar la detección temprana de incidencias. • Documentar buenas prácticas y formar a usuarios técnicos en el uso de las herramientas.

Role Description We are seeking an experienced Lead Rulebook Configurator to lead the configuration and implementation of insurance products, pricing models, underwriting rules, and workflow components within Verisk Rulebook / Sequel Rulebook. The role sits at the intersection of insurance domain, pricing model interpretation, rules configuration, business analysis, and stakeholder engagement. The individual will work closely with senior stakeholders from Underwriting, Actuarial, Operations, Product, IT, and Change teams, primarily in the London Market / specialty insurance environment. The ideal candidate will have a strong configuration mindset, excellent analytical ability, hands-on experience with Rulebook or similar rules/rating platforms, and the confidence to translate complex Excel-based pricing models and underwriting guidelines into structured, governed Rulebook configurations. Key Responsibilities - Lead the configuration of insurance products, rating algorithms, underwriting rules, referral rules, eligibility rules, authority checks, and workflow logic within Rulebook. - Convert Excel-based pricing models into Rulebook-compatible configuration components, ensuring calculation accuracy and business alignment. - Configure rating tables, factors, modifiers, risk attributes, premium calculations, validations, and business rules. - Configure and maintain Rulebook pages, page flows, page linking, product structures, and user journeys. - Support document generation logic, quote outputs, pricing worksheets, and downstream data outputs where applicable. - Ensure reusable configuration patterns are applied across products/classes to improve maintainability and consistency. Business and Domain Analysis - Work with underwriters, actuaries, operations SMEs, and product owners to understand pricing intent, risk appetite, referral logic, and underwriting guidelines. - Challenge and clarify ambiguous business rules before configuration. - Translate business requirements into clear configuration specifications and implementation-ready artefacts. - Identify gaps, inconsistencies, or risks in pricing spreadsheets, underwriting guides, or product documentation. - Support impact analysis for pricing changes, product enhancements, and model version updates. Stakeholder Management and Communication - Act as a primary configuration lead in workshops with senior London-based business stakeholders. - Explain configuration design, rule logic, testing outcomes, issues, and trade-offs in clear business language. - Facilitate discussions between business SMEs, actuaries, developers, testers, architects, and delivery leads. - Provide structured status updates, risk/issue summaries, and decision points to project leadership. - Ensure business stakeholders understand how configured rules reflect their underwriting and pricing requirements. Testing, Validation, and Governance - Define and execute rule configuration testing, scenario testing, regression testing, and spreadsheet-to-Rulebook reconciliation. - Validate Rulebook outputs against source Excel models, expected pricing outcomes, underwriting rules, and edge-case scenarios. - Support SIT, UAT, defect triage, root-cause analysis, and defect resolution. - Maintain configuration documentation, traceability, version control, and audit evidence. - Ensure configurations support governance, auditability, and controlled deployment of pricing/underwriting changes. Technical Skills - Mandatory: - Strong Rulebook configuration mindset: ability to translate business rules into structured configuration. - Strong Excel skills, including ability to understand complex formulas, rating sheets, lookup tables, factors, and calculation flows. - Good understanding of XML and structured configuration files. - Ability to understand rule hierarchies, conditional logic, validations, decision trees, and calculation dependencies. - Experience with configuration testing, regression testing, and price-output reconciliation. - Familiarity with JIRA, Confluence, Azure DevOps, or similar delivery tools. - Ability to document configuration logic clearly. - Desirable: - Understanding of APIs, JSON, SQL, or data mapping. - Exposure to rating services, quote/bind platforms, broker portals, or delegated authority platforms. - Experience with document production, workflow configuration, or downstream integration. - Familiarity with rule deployment, release management, and environment promotion. Insurance Domain Knowledge - Insurance product structure - Submission, quote, bind, endorsement/MTA, renewal workflows - Rating factors, adjustments, deductibles/excesses, limits, commissions, taxes/fees where applicable - Underwriting appetite and referral logic - Authority limits and exception handling - Pricing model governance and audit trail - Deep actuarial expertise is not required, but the candidate must be able to understand pricing spreadsheets and hold credible conversations with pricing stakeholders.

Role Description We are looking for a highly skilled GPU Compute, MLIR Compiler, and Kernel Optimization Engineer with deep expertise in GPU compute, MLIR-based code generation, and end-to-end performance optimization for AI workloads. In this role, you will design, optimize, and deploy high-performance GPU compute kernels, build and extend MLIR compiler backends, and collaborate closely with ML, runtime, and hardware teams to push the limits of performance on modern GPU architectures. - Develop and optimize GPU compute kernels targeting OpenCL and Vulkan compute backends for high-throughput AI/ML workloads. - Design, build, and extend MLIR dialects across multiple abstraction levels—including frontend dialects, graph-level IR, tensor IR (e.g., Linalg, Tensor, TOSA), and runtime/low-level dialects—to enable efficient end-to-end model compilation. - Implement and maintain MLIR-based compiler passes and transformations, including tiling, fusion, bufferization, vectorization, and lowering pipelines targeting OpenCL and Vulkan GPU backends. - Conduct profiling and bottleneck analysis of compiled kernels using GPU counters and vendor-specific profilers, and drive performance improvements through compiler-level optimizations. - Build and maintain GPU runtime infrastructure for both OpenCL and Vulkan, including memory management, pipeline setup, command buffer orchestration, and resource scheduling. - Develop and extend code generation pipelines, enabling automatic lowering from tensor IR through MLIR to efficient OpenCL and Vulkan GPU kernels. - Implement performance-critical schedules—including tiling, loop fusion, parallelism, and caching strategies—within MLIR-based backends targeting OpenCL and Vulkan runtimes. - Collaborate with framework teams to optimize end-to-end model lowering for computer vision and LLM workloads using MLIR compilation stacks. - Design and implement robust compiler and runtime components using modern C/C++, leveraging advanced programming paradigms for high-performance systems. Qualifications - Strong hands-on experience with the MLIR framework, including authoring and extending custom dialects, writing compiler passes, and building end-to-end lowering pipelines. - Deep expertise across MLIR abstraction levels: - Frontend dialects – ingestion and representation of ML models (e.g., TOSA, StableHLO, ONNX-MLIR) - Graph-level IR – high-level operation fusion, shape inference, and graph transformations - Tensor IR level – structured operation representation using Linalg, Tensor, and Vector dialects; tiling and fusion strategies - Runtime/low-level dialects – Bufferization, MemRef, SCF, GPU, and LLVM dialects for final code generation - Strong hands-on experience in OpenCL programming, including kernel development, memory model, work-group/work-item optimization, and OpenCL runtime management. - Solid understanding of Vulkan compute programming, including descriptor management, compute pipelines, synchronization primitives, and Vulkan runtime internals. - Strong understanding of GPU architecture, memory hierarchies, and asynchronous compute. - Proficiency in C/C++ for system-level development. - Experience with kernel profiling and bottleneck analysis on GPU platforms. - Strong background in machine learning fundamentals, covering both Computer Vision (CV) and Large Language Model (LLM) workloads. Requirements - Must-have skills: gpu computing, MLIR, C/C++ - Good-to-have skills: vulkan, Kernel, OpenCL Benefits - Salary range: Rs 2000000 - Rs 10000000 (ie INR 20 - 100 LPA) - Min Experience: 3+ years - Location: India - Job Type: full-time