• Lead the engineering and sustainment of Windows server platforms supporting critical digital services within ASD. • Design, build and operate core Windows services including Active Directory, DNS, PKI, Remote Desktop Services and WSUS. • Lead complex systems design activity balancing functional and non-functional requirements. • Integrate and support management and security software, configurations and MFA solutions across the Windows estate. • Develop server automation and scripting to streamline build, configuration and operational tasks. • Take responsibility for systems installation, migration and decommissioning projects.

Role Description - Work with the ServiceNow team to implement solutions across global locations - Provide technical expertise in ServiceNow ITOM module, especially Service Mapping - Design and implement ServiceNow integrations - Understand business needs and align them with standardized processes and system design - Develop and implement technical solutions on the ServiceNow platform - Perform component integration testing and ensure quality delivery - Support UAT and production deployments - Collaborate with cross-functional teams for seamless project execution - Troubleshoot and resolve technical issues - Ensure adherence to best practices and continuous improvement - Participate in design and code reviews and provide recommendations Qualifications - Bachelor’s or master’s degree in computer science, Information Technology, or a related field Requirements - Experience - 5.5+ years - Strong experience in ServiceNow ITOM, CMDB, and Service Mapping - Hands-on experience in ServiceNow integrations - Experience in other modules like SPM or GRC or HRSD along with ITIL knowledge - ServiceNow certification (any module) - Strong understanding of ITOM and Service Mapping concepts - Ability to translate business requirements into technical solutions - Experience in developing and implementing technical solutions and performing integration testing - Experience with ServiceNow scripting (Business Rules, Client Scripts, UI Policies, UI Actions) - Good understanding of CMDB data model and relationships - Strong communication and stakeholder management skills - Ability to work in a global delivery environment Company Description We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital, and our people exist everywhere in the world (17700+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in.

Role Description We’re hiring a Forward Deployed Engineer to work directly with customers as they integrate our knowledge graph into their own systems. Our customers are typically data science and bioinformatics teams in pharmaceuticals or biotechs. You’ll work closely with customer technical teams to get our data products into production. That might mean loading the graph into Neo4j, exposing it through APIs, flattening it into analytical warehouses, or helping customers use it in LLM and agent workflows. Sometimes the customer team will own most of the implementation; sometimes you’ll build large parts of it yourself. In this highly impactful role; you’ll take technical ownership from trial through to a working deployment. The role is roughly 70% customer-facing delivery work and 30% contribution to our core platform. Based in our Engineering team you’ll blend customer delivery with engineering in our core platform team; turning repeated customer problems into reusable product capabilities. Key Responsibilities - Lead customer integrations - Design integrations for AI and agent workflows - Contribute to technical scoping - Drive productisation - Contribute to the platform Qualifications - Strong experience building and deploying machine-learning-based data systems - Comfortable working with the core building blocks of these systems - Machine learning or data science background is valuable - Deep experience in either machine learning or data engineering is essential Requirements - Proven experience deploying NLP systems or LLM-powered features into production - Familiarity with recommendation and retrieval systems, retrieval-augmented generation (RAG) and vector databases - Practical experience building or debugging LLM-driven workflows - Demonstrable experience designing and running model evaluation and monitoring frameworks - Hands-on experience fine-tuning transformer-based models for domain- or task-specific use cases - Proven track record of building evaluation datasets or benchmarks from scratch - Comfortable moving between different architectural approaches for storing and accessing data - Experience building MCP servers and developing APIs with a focus on ease of LLM integration - Experience with graph databases - Neo4J preferred - Experience managing schema evolution in production - Hands-on experience building or maintaining dbt projects (or equivalent transformation tooling) - Experience working with distributed compute systems such as Spark or Beam - Experience running production orchestration systems such as Airflow, Dagster, or Prefect - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) - Ability to communicate effectively with both highly technical customer groups and internally - High personal quality standards, bringing positive energy and able to thrive with ambiguity in a scale-up environment Benefits - Competitive salaries and share options - Enhanced family leave - Significant opportunities for professional development - Genuine Flexibility: Fully remote business with colleagues across the globe - Cutting-Edge Technology: Work with the latest software tools and technologies

Role Description - Help build and improve automation, tooling, and infrastructure that supports AI workloads - Support the development of operational systems and platform services - Assist in defining and maintaining basic SLOs/SLIs and monitoring dashboards - Participate in incident response, troubleshooting, and post-incident reviews - Investigate and help resolve performance and reliability issues across systems - Collaborate with Engineering, Networking, and Infrastructure teams to improve system stability - Contribute to improving availability, scalability, and operational efficiency - Learn from senior engineers and grow your expertise in reliability engineering Qualifications - 2–5 years of experience in Site Reliability Engineering, Systems Engineering, or Software Engineering in Data Center Environment - 2+ years programming skills (e.g., Python, Go, or similar) with interest in automation and tooling - Working knowledge of Linux systems, networking concepts, and distributed systems - Experience troubleshooting system or application issues in production environments - Familiarity with monitoring or observability tools (e.g., logs, metrics, dashboards) - Strong willingness to learn and improve reliability and operational practices - Ability to work in fast-paced environments and collaborate across teams Requirements - Exposure to cloud platforms, Kubernetes, or virtualized/bare-metal environments - Experience in AI, GPU workloads, or high-performance computing (HPC) - Basic understanding of high-performance networking concepts (e.g., InfiniBand, RDMA) - Exposure to production monitoring or alerting systems at small or medium scale Benefits - Collaborative, supportive, and innovative environment - Highly competitive package (base + equity) with reviews every 12 months - Dynamic progression plan tailored to your ambitions - Human-First Flexibility: autonomy to shape your day around life's moments - Competitive benefits package including medical, dental, vision, flexible paid time off, parental leave, and retirement plan participation