Jobs at BGTS

Build compliant, high-quality real-time data pipelines for CDR, network telemetry, and customer data. Enable Kafka and Flink streaming for AI use cases, implement data quality, lineage, and governance controls, manage feature engineering pipelines for machine learning models, and ensure compliance with data privacy regulations. Success is measured through real-time readiness, data quality, and pipeline reliability.

Lead Salesforce-to-Dynamics 365 CRM migrations by assessing environments, defining migration strategies, mapping and transforming data, configuring Dynamics 365, migrating integrations, supporting testing and cutover, and providing training and post-go-live support. The role requires strong Salesforce, Dynamics 365, Dataverse, Power Platform, data migration, integration, stakeholder management, and Agile delivery expertise.

Own the AI platform roadmap, backlog, use-case prioritization, stakeholder alignment, adoption, usability, cost transparency, and ROI tracking across telecommunications domains. The role focuses on delivering business value through revenue growth, churn reduction, automation, and network optimization while aligning platform delivery with business-unit needs and strategic priorities.

Own and configure the SAP SuccessFactors Employee Central module, including data standards, documentation, enhancements, support, issue resolution, release management, data quality, and reporting. Translate HR requirements into system solutions, improve and automate processes, troubleshoot integrations and workflows, collaborate with SAP Support, and advise HR, IT, leadership, and global stakeholders on HR transformation initiatives.

Ensure the reliability, performance, availability, and cost efficiency of AI services in production telco environments. Define SLIs and SLOs, monitor model drift and AI performance, manage incident response and root cause analysis, support disaster recovery and high availability, and optimize GPU usage and inference scaling for mission-critical fraud and network operations use cases.

Owns enterprise AI architecture across telecom network, customer, and revenue domains. Defines scalable GenAI, ML, and agentic system architectures; integrates AI with OSS/BSS platforms and network data sources; establishes RAG, real-time inference, and AI-agent reference architectures; and develops governance, TRiSM, model-risk, security, compliance, and multi-country deployment standards across cloud, edge, latency, and data-sovereignty requirements.

Product Engineer responsible for taking digital product features from discovery through production and support. The role involves translating business needs into scalable technical solutions, developing secure and maintainable software, collaborating with multidisciplinary teams, and contributing to engineering practices and AI-assisted development. The engineer will work with stakeholders, product owners, testers, designers, and fellow engineers while supporting continuous improvement and operational stability.

Identify and pursue UK sales opportunities, manage the full sales cycle from prospecting through closing, exceed revenue targets, build lasting client and partner relationships, conduct targeted outreach and networking, negotiate effectively, overcome objections, and adapt sales strategies based on industry trends.

Build and operate a shared AI platform for telecom squads. Responsibilities include developing model-serving, vector database, feature store, and prompt orchestration services; enabling self-service APIs, SDKs, and pipelines; integrating Kafka, streaming, and data lakes; managing GPU workloads and inference scaling; and supporting low-latency applications such as real-time fraud detection.

Lead the EMEA Big Data Analytics and Data Insights team, managing data engineers and scientists, setting objectives, allocating resources, and conducting reviews. Transform complex data into enterprise data-layer insights, support IT projects, contribute technically, and help shape global data warehouse, data lake, and Lakehouse architecture. The role requires strong leadership, data architecture expertise, business collaboration, and approximately 10% travel.

Build and integrate AI-powered features across telecommunications customer apps, call centre tools, and network operations. Develop prompt-engineering solutions and agent workflows, connect AI capabilities to APIs, mobile applications, and enterprise systems, and collaborate with agile product squads. Success is measured through feature adoption, customer experience improvements, and reduced manual effort.

Leads an EMEA data engineering and data science team, manages objectives, performance reviews, and resource allocation for IT projects. Transforms complex data into enterprise data layers, identifies insights and data quality issues, contributes as a player-coach, and helps shape data warehouse, data lake, Lakehouse, and broader system architecture.

Lead technical discovery and translate business needs into target architectures, transformation roadmaps, and delivery plans. Own technical content for RFPs, RFIs, and tenders; design demos, proofs of concept, and reference architectures; shape commercial models and estimates; advise financial-services clients on practical AI adoption and governance; bridge presales commitments into delivery; and develop reusable solution assets and enablement materials.

Design and improve reusable solution architectures for AI, data, and API applications built primarily on Azure and Databricks. Define integrations across cloud services, Databricks, internal platforms, and third-party systems. Support AI modernization, security assessments, architecture documentation, and implementation guidance while coordinating with delivery, platform, security, and business stakeholders.

Develop and maintain Java backend services and desktop applications using Spring Boot, JavaFX, and Java Swing. Build REST and SOAP integrations, implement business logic and application security, write unit tests, participate in code reviews, and support CI/CD deployments. Collaborate with business teams, analysts, and developers in an Agile environment while troubleshooting technical issues and maintaining clean, reliable code.

Build and maintain data-driven solutions for a banking client by onboarding data sources, developing reports, enhancing a SQL data warehouse, and maintaining pipelines. Integrate data from staging through data marts, ensure data quality, optimize T-SQL procedures and queries, and support legacy MS Access, text-file, and Excel environments. Collaborate with business stakeholders and cross-functional teams to deliver reliable, scalable data solutions.

Lead an information security project replacing an internally developed firewall governance solution with an off-the-shelf SaaS firewall management platform.

Lead and support SAP SuccessFactors Talent Management implementations, including Performance & Goals, Succession & Development, and Onboarding. Analyze business processes, configure solutions, manage permissions, gather requirements, conduct workshops, train users, provide ongoing support, and coordinate testing, upgrades, and release management. Collaborate with international HR stakeholders and manage deployment and enhancement projects while applying SAP best practices.

Drive business growth across Germany by identifying and winning new B2B technology-services opportunities. Build and manage a sales pipeline from prospecting through signed contracts, understand client needs, connect them with BGTS solutions, collaborate with technical and delivery teams on proposals, and represent the company at client meetings and industry events.

Automate AI and machine learning system lifecycles from experimentation through production. Build CI/CD and continuous training pipelines, manage model versioning, rollback and A/B testing, provision AI infrastructure with infrastructure as code, and ensure model reproducibility, monitoring, and auditability.