Manager

• Analyze data and gather business requirements to support decision-making.
• Provide insights to stakeholders and ensure data accuracy.
• Develop reports and implement process improvements.
• Perform basic coding and scripting in Python/SQL for data extraction, transformation, and analysis.

Lead Assistant Manager

Data Scientist

• Perform data profiling, reconciliation, and validation to ensure accuracy, completeness, and consistency across procurement datasets
• Analyze data discrepancies, identify root causes, and implement corrective measures with detailed documentation
• Execute post-load validation checks and ensure adherence to SAP data standards, governance policies, and quality frameworks
• Design and optimize scalable data workflows for efficient extraction, transformation, and processing
• Build and deploy ML-based supplier scoring models to automate vendor evaluation and shortlisting
• Develop NLP and LLM-powered pipelines to analyze proposals, SOW documents, and other sourcing artifacts
• Leverage LLMs to automate RFx document generation and review, ensuring consistency, completeness, and alignment with business requirements
• Automate market research workflows using web scraping and generative AI to generate supplier landscape reports and insights
• Design procurement analytics dashboards and predictive models to track sourcing pipeline health and forecast cycle timelines, utilizing SQL, Power BI, or Tableau
• Implement anomaly detection models on procurement spend data to identify contract leakage, while applying NLP techniques (NER, embeddings, RAG) and leveraging LLM APIs (OpenAI, AWS Bedrock, Azure OpenAI), with proficiency in Python and ML frameworks (scikit-learn, spaCy, LangChain) to enable end-to-end procurement automation

Data Science – Gen AI Engineer

Product Manager

• Design and implement product strategies
• Optimize product performance and market fit
• Ensure product meets customer requirements
• Provide product management support
• Collaborate with stakeholders.

Digital Product Owner

Systems Engineer

• Analyze existing application architectures, system workflows, integrations, and business processes to identify gaps and optimization opportunities.
• Gather, document, and translate business requirements into detailed functional and technical specifications.
• Develop system design documents, process flow diagrams, data flow diagrams (DFDs), use cases, and interface specifications.
• Evaluate system performance, scalability, and reliability, recommending technology enhancements and modernization strategies.
• Collaborate with architects, developers, data engineers, and QA teams to design and implement enterprise-grade solutions.
• Lead end-to-end technology projects including application implementations, cloud migrations, data platform initiatives, and system integrations.
• Define project scope, technical deliverables, milestones, resource plans, and implementation roadmaps.
• Manage Agile/Scrum ceremonies including sprint planning, backlog grooming, stand-ups, and retrospectives.
• Track project progress, dependencies, technical risks, and mitigation plans.
• Coordinate cross-functional teams including development, infrastructure, data engineering, cybersecurity, and business teams.
• Ensure successful deployment, testing, and production release of technology solutions.
• Analyze and document system interfaces, and data integration workflows.
• Collaborate with development teams to define integration requirements between enterprise applications and cloud platforms.
• Support data mapping, transformation logic, and data quality validation activities.
• Support cloud transformation initiatives involving AWS, Azure, or GCP environments.
• Work with infrastructure and platform teams to ensure system reliability, security, and scalability.
• Evaluate emerging technologies and recommend solutions to improve operational efficiency and business outcomes.
• Ensure compliance with enterprise architecture standards, security controls, and governance frameworks.
• Develop and maintain technical documentation, architecture diagrams, requirement traceability matrices, and project artifacts.
• Create project dashboards, status reports, and executive presentations to communicate progress and risks.
• Establish KPIs and monitoring metrics to measure system performance and project success.
• Support audit, compliance, and governance activities through proper documentation and controls.

Computer Systems Analyst – Project Manager

Analyst

• Collect, clean, and analyse user and product data from multiple sources.
• Perform exploratory data analysis (EDA) to identify trends and user interaction patterns.
• Assist in building and evaluating basic machine learning and GenAI models (e.g., chatbots, text generation, recommendations).
• Support user research and translate insights into design solutions.
• Create wireframes, prototypes, and high-fidelity mock-ups
• Apply prompt engineering and generative AI tools (e.g., ChatGPT, DALL·E, Miro AI) to generate design variations, automate prototyping, and personalize user experiences
• Support UX/UI teams by translating data insights into design improvements.
• Conduct A/B testing and analyse results to optimize user experience and engagement.
• Help develop simple prototypes for AI-powered features.
• Create dashboards, reports, and visualizations for stakeholders.
• Ensure data quality, accuracy, and consistency in all analyses.

Backend Engineer

Python Developer

SDET

• Test Engineers will be responsible for the design, development, testing, maintenance, and support data assets including; Azure Data Lake and data warehouse development, modeling, package creation, SQL script creation, stored procedure development, integration services support among other responsibilities.
• Candidate have at least 3-5 years hands-on Azure experience as a Test Engineer, must be an expert in SQL and have extensive expertise building data pipelines. Candidate will be accountable for meeting deliverable commitments including schedule and quality compliance. This Candidate must have skills to plan and schedule own work activities, coordinate activities with other cross-functional team members to meet project goals.

Test Engineer

Artificial Intelligence

• Design and deploy intelligent automation and agentic AI solutions that save time, slash errors, and WOW stakeholders.
• Collaborate on AI strategies, ensuring our clients’ critical needs are met.
• Blend tech prowess with domain insights — think big, fail fast, innovate.
• Evangelize best practices in this thrilling fusion of AI and business.

Agentic AI, GEN AI

• Lead the end-to-end architecture, design, and technical direction for Generative AI solutions supporting business process automation in the Life & Annuities ecosystem.
• Define scalable, secure, and reusable architecture patterns for AI-enabled workflows across policy administration, underwriting, servicing, document processing, and partner integrations.
• Partner with business, operations, product, and engineering teams to identify high-value AI use cases and translate them into implementable technical solutions.
• Architect enterprise-grade AI solutions using modern patterns such as Retrieval-Augmented Generation (RAG), prompt orchestration, agent-based workflows, vector search, and human-in-the-loop controls.
• Design and oversee integrations between AI services and core insurance platforms, TPA systems, underwriting tools, CRM platforms, document repositories, APIs, messaging systems, and third-party data providers.
• Establish solution standards for security, privacy, auditability, explainability, observability, and compliance in regulated insurance environments.
• Evaluate and recommend appropriate cloud, data, and AI technology stacks, frameworks, and tooling aligned with enterprise architecture standards.
• Provide technical leadership to cross-functional delivery teams, including conducting architecture reviews, defining guardrails, mentoring engineers, and resolving complex design challenges.
• Drive non-functional architecture requirements including performance, scalability, resiliency, model monitoring, and operational support readiness.
• Collaborate with enterprise architecture, security, data, and governance teams to ensure AI solutions are aligned with organizational policies and long-term technology strategy.

Technical Architect – Generative AI, Life & Annuities Insurance

• Oversee day to day operations to ensure efficiency and effectiveness in all business functions, including staffing and inventory management.
• Lead, train and mentor staff members, ensuring high levels of engagements and productivity.
• Monitor and ensure excellent client service is always provided, addressing escalated client issues and resolving them in a timely manner.
• Maintaining comprehensive financial transaction records including daily over payments.
• Excellent multitasking and time management
• Analyzing the weekly and monthly reports, helping team on the clarifications.

Assistant Manager – Claims Audit

Data Engineer

• Design, build, and maintain scalable data platforms and services
• Implement data pipeline solutions in Python and cloud platforms like AWS
• Optimize data delivery and reduce cloud costs through automation
• Monitor Data Quality, Observability, Governance, and Lineage
• Collaborate with internal teams and client stakeholders
• Write unit/integration tests and document design/implementation

Lead Data Engineer

Executive Assistant

• Own end-to-end delivery of AI/GenAI programs across multiple accounts
• Drive timely, high-quality execution with clear business outcomes (revenue, cost, efficiency)
• Establish delivery governance, KPIs, and performance tracking
• Manage a portfolio of AI initiatives (GenAI, automation, advanced analytics)
• Lead program planning, risk management, and cross-functional alignment
• Ensure scalable delivery using Agile, MLOps, and LLMOps practices
• Act as a trusted advisor to senior client stakeholders
• Translate business problems into AI-led solutions and execution roadmaps
• Drive client satisfaction, retention, and growth
• Guide teams on LLM-based applications, RAG architectures, and agentic workflows
• Ensure solutions meet enterprise standards (scalability, security, governance)
• Promote use of reusable assets and accelerators
• Support AI solutioning for large deals and strategic bids
• Partner with sales to develop value propositions and proposals
• Identify expansion opportunities within accounts
• Build and lead high-performing AI teams (architects, data scientists, engineers)
• Mentor leaders and drive capability development in GenAI
• Foster a culture of ownership, innovation, and delivery excellence

Senior Assistant Vice President

Support Engineer

• Maintain web applications using .NET technologies.
• Work on both backend APIs and frontend components.
• Troubleshoot, debug, and resolve application bugs and production issues.
• Write and optimize SQL queries for data retrieval and updates.
• Collaborate with cross-functional teams to analyze requirements and deliver solutions.
• Maintain code quality through best practices and documentation.
• Perform debugging, and performance optimization.
• Support deployment and maintenance of applications in different environments.

Technical Support Engineer

Vice President

• Client Relationship Management: Establish and maintain relationships with assigned clients, addressing their day-to-day needs and resolving issues as they arise.
• Account Support: Assist with the execution of account plans, including managing schedules, coordinating with internal teams, and ensuring timely delivery of services or products.
• Reporting and Documentation: Track and report on account activity, including status updates, performance metrics, and client feedback.
• Sales and Upselling: Identify opportunities for upselling and cross selling additional services or products within the scope of the account.

EXL