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This role involves driving AI, Data, and Digital sales in the financial services sector, focusing on complex enterprise deals and relationship management.

The Senior Platform Engineer will design and optimize a platform using Python, DevOps, and ModelOps, managing application lifecycles and collaborating with teams for high-performance deployments.

Design, build, and deploy production-ready ML models emphasizing recommendation and ranking systems. Apply NLP and behavioural analytics to large-scale datasets using Databricks and Spark. Run experiments (A/B tests), monitor and optimise live models, and collaborate with engineers and product teams to deliver measurable business impact.

Lead and mentor a Data Engineering team to design, build, and optimize scalable Microsoft-based data platforms (Fabric, Databricks, Synapse, Azure). Develop PySpark/Spark SQL pipelines, orchestrate with ADF/Synapse/Fabric Pipelines, manage Azure DevOps and CI/CD, scope tasks, review code, and drive Agile delivery while acting as technical SME and stakeholder partner.

Lead end-to-end fullstack and Generative AI solutions: architect, build, deploy, and operate production systems. Design LLM/RAG capabilities, own DevOps (CI/CD, IaC, containers, orchestration), drive technical proposals with customers, enforce engineering standards, and mentor engineers while supporting pre-sales and discovery.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.

As a Data Scientist in Pre-Sales, you will implement data-driven solutions, support sales with analytics expertise, and collaborate with technical teams on AI and machine learning projects.

Lead technical initiatives within Kallidus, building and optimizing scalable solutions, mentoring junior engineers, and collaborating across teams.

Design and develop data models, ETL processes, and cloud-based data solutions using Azure and various big data technologies. Support report generation and data analysis.