Auditor

• Performing physical and remote audits of insured’s business
• Interviews, investigates, collects, and records information to be used in a written report that is provided to the insurance carrier

Insurance Field Auditor

• The Premium Insurance Field Auditor conducts insurance policy audits for Worker’s Compensation, Auto and General Liability policies.
• This is done by auditing the policyholder’s records according to client company standards.
• If you are looking for a fast paced, self-motivating work environment from home, this job may be for you!
• Working from your home office, this role requires scheduling appointments with the insured to be audited, and travel on an average of 4 days per week within your assigned territory to meet with the insured and obtain necessary documentation for our insurance company client audits all while adhering to customer requirements and quality standards.
• Territory: Miami, FL. and surrounding areas

Premium Insurance Field Auditor

Developer Relations

• Define and execute the Developer Experience and Engineering Operations roadmap, aligned to EXL's Products, Platforms and AI engineering priorities.
• Identify the highest-friction points in the engineering lifecycle through developer interviews, workflow analysis, metrics, delivery retrospectives and leadership input.
• Establish practical engineering standards, golden paths, reusable templates, delivery playbooks and reference workflows that help teams build and operate solutions consistently.
• Partner with Architecture, Platform Engineering, Cloud, DevOps, Security and Product Engineering teams to improve CI/CD, local development, build and test automation, environment management, release readiness, observability and operational feedback loops.
• Drive responsible AI adoption across the SDLC, including AI coding assistants, code review support, test generation, documentation automation, knowledge retrieval and agentic workflow opportunities.
• Create clear guidance for AI-assisted engineering practices, including appropriate use, security boundaries, data handling, prompt and context patterns, review expectations and quality controls.
• Evangelise EXLerate.ai and related platform capabilities across engineering teams, helping teams understand where the platform should be used, how reusable assets should be created, and how AI-enabled solutions should be governed and operated.
• Develop enablement programmes such as communities of practice, office hours, playbooks, internal demos, workshops, onboarding journeys and hands-on adoption campaigns.
• Own the developer tooling adoption approach across IDEs, source control, CI/CD, documentation, internal portals, AI tools and engineering intelligence platforms, ensuring tools are useful, governed and adopted for measurable value.
• Define a measurement framework for Developer Experience, including adoption, satisfaction, friction reduction, cycle time, build and test reliability, onboarding time, tool effectiveness, quality signals and AI-assisted engineering outcomes.
• Create structured feedback loops so engineering teams can contribute to standards, improve shared workflows and influence the roadmap for internal platforms and tools.
• Support engineering leaders in improving delivery transparency, operating cadences, decision management, documentation discipline and cross-team dependency management.
• Ensure Developer Experience improvements are aligned with security, compliance, responsible AI, architecture governance and operational risk expectations.

Developer Experience Lead

Software Engineer

• Lead and develop a globally distributed architecture team across Ireland, the UK, the US and India, with clear roles, accountabilities and standards of technical leadership.
• Define the architecture operating model, including governance forums, review patterns, decision rights, architecture artefacts and escalation paths.
• Chair and mature the Architecture Review Board, ensuring architectural decisions are pragmatic, risk-aware and aligned to EXL standards and business priorities.
• Publish, maintain and drive adoption of engineering principles, standards and reference architectures across EXL's Products, Platforms and AI solutions.
• Own the EXL Technology Radar, using it to define and communicate technology strategy, adoption guidance and lifecycle decisions across the organisation.
• Establish named architectural ownership and reusable patterns across AWS, Azure and Google Cloud, with an emphasis on secure, scalable and portable platform design.
• Partner with product, platform, engineering, InfoSec, data, finance and delivery leaders to align technical strategy with product roadmaps, client commitments and operational constraints.
• Define the Developer Experience strategy across tools, delivery processes, internal platforms, documentation, templates, reusable components and AI-assisted engineering practices.
• Ensure engineering teams have access to the right tooling and processes to deliver value effectively, with adoption measured through outcomes rather than vanity metrics.
• Lead engineering FinOps practices for cloud and tooling spend in partnership with Finance, cloud platform and engineering leaders, including cost visibility, tagging discipline, optimisation opportunities, licence consolidation and executive reporting.
• Provide senior client-facing architecture support for strategic pursuits and client conversations, including solution shaping, estimation input, technical narrative, architectural trade-off analysis and risk assessment.
• Stay technically engaged by leading complex architecture reviews, advising on strategic designs and remaining credible with senior architects and engineers.
• Own the team's budget, objectives, operating cadence, executive reporting and architecture metrics pack.

Head of Architecture and Engineering Operations

• Develop, maintain, and optimize SAS programs and batch jobs.
• Write complex SQL queries, stored procedures, and data extraction scripts.
• Perform data analysis, validation, cleansing, and transformation activities.
• Work with large-scale databases and data warehouses.
• Create reports, dashboards, and analytical datasets using SAS.
• Collaborate with business analysts, data engineers, and stakeholders to understand requirements.
• Troubleshoot and resolve data and performance-related issues.
• Ensure data accuracy, integrity, and compliance with standards.
• Participate in code reviews, documentation, and deployment activities.

SAS Developer

Consultant

• Not applicable for internal candidates

Consultant I

Sales

• Lead the design and implementation of B2B Marketing Use Cases around Customer Journey Optimization
• Collaborate with clients and stakeholders to translate business requirements into scalable technical solutions
• Drive marketing transformation initiatives using Salesforce Marketing Cloud and related tools
• Lead and mentor a team of 1-2 developers and consultants
• Design and implement customer segmentation strategies and targeted marketing campaigns
• Ensure best practices in solution design, data management, and system integration
• Provide technical leadership across Salesforce Einstein and Agentforce capabilities

Salesforce Marketing Cloud – Agentforce

Actuary

• Pricing analyses for actuarial relevant projects
• Collaborate with cross-functional teams
• Develop pricing strategies based on actuarial models
• Contribute to financial forecasting and analysis

Actuarial Pricing Analyst

Backend Engineer

• Design, develop, and maintain both front-end user interfaces and back-end server-side logic.
• Development of RESTful APIs and microservices using Java frameworks (Spring Boot, JPA, Hibernate, etc.)
• Implement responsive frontends using JavaScript/Typescript.
• Manage scalable database schemas (SQL/NoSQL) and ensure efficient data storage and retrieval
• Improve application speed and scalability through code refactoring, caching, and front-end optimization
• Write and execute unit, integration, and end-to-end tests to ensure high software reliability and security
• Partner with designers and product managers to turn wireframes and requirements into functional, production-ready code

Java Full Stack Developer

Data Scientist

• Develop and evaluate LLM-powered solutions such as summarization, classification, extraction and conversational assistants**
• Design prompt strategies, RAG architectures, and fine-tuning/adapter approaches where appropriate**
• Apply NLP and ML methods: text classification, topic modeling, semantic search, embeddings, clustering, regression/causal inference as needed**
• Develop Python-based prototypes and evaluation frameworks for LLM and GenAI use cases**
• Advanced use of object-oriented programming and functional programming patterns for ML workflows

Data Scientist – GenAI Engineer

Artificial Intelligence

• Build and maintain strong relationships with key banking and capital markets clients.
• Act as the primary contact for strategic discussions, understanding client needs and identifying opportunities for value creation through consultative engagement.
• Lead development of tailored technical proposals in collaboration with cross-functional teams.
• Design innovative solutions in areas like data modernization, digital transformation, and integration, ensuring proposals are practical, competitive, and aligned with best practices.
• Monitor account performance and drive growth through upsell and cross-sell opportunities.
• Achieve revenue targets by expanding service offerings and leveraging emerging technologies such as AI, cloud, and data platforms.
• Coordinate across advisory, technology, and operations teams to ensure seamless delivery.
• Stay current on industry trends, regulatory changes, and competitive dynamics.
• Contribute to thought leadership through client presentations, webinars, and whitepapers.
• Mentor and guide junior team members, fostering a high-performance culture and building capabilities in client management and solution design.

Data/AI Client Engagement Lead – Senior AVP

Data Engineer

• Lead and manage **end-to-end Data Engineering delivery** across projects and initiatives
• Act as the **primary technical owner** for data pipelines, architecture, and platform design
• Mentor and guide a team of data engineers, ensuring best practices and coding standards
• Design, build, and optimize **scalable data pipelines** on GCP
• Define and implement **modern data architectures** (data lake, lakehouse, warehouse)
• Ensure high performance, reliability, and data quality across pipelines
• Partner closely with **Data Science teams** to enable ML/AI workflows
• Translate business and modeling requirements into **optimized data structures**
• Support feature engineering, model training, and deployment pipelines
• Design **logical and physical data models** for analytics and ML use cases
• Implement **dimensional modeling (Star/Snowflake schemas)** and data vault where applicable
• Optimize datasets for performance, scalability, and usability
• Build and manage solutions using GCP services such as: **BigQuery, Cloud Composer (Airflow), Cloud Storage, Dataproc**
• Ensure security, governance, and cost optimization on GCP

Senior GCP Data Engineer

DevOps Engineer

• Collaborate closely with data teams to support the development and deployment of innovative and efficient data solutions.
• Respond to and fulfill platform requests from various data teams of the client, including internal business stakeholders, data analytics professionals, data engineers, and quality assurance teams.

AWS DevOps Engineer

Solutions Engineer

• Partner with sales and industry teams to design client-ready demos, proof-of-concepts, and technical solution blueprints.
• Present complex architectures to stakeholders.
• Architect distributed, scalable, and resilient data and AI platforms for presales demonstrations.
• Define observability standards for demo and enterprise environments.
• Collaborate with product, data science, engineering, and governance teams.
• Stay ahead of hyperscaler advancements, AI/ML frameworks, and orchestration patterns.
• Mentor presales engineers and junior architects in solution design and client presentation skills.

Solution Architect – Data, AI Solutions

Business Analyst

• Creating and producing project-specific technical content, including user manuals, requirements, design, test, and operations documents.
• Assisting with production support issues as they arise.
• Taking care of issues raised through performance testing.
• Troubleshooting application-specific issues.
• Understanding business requirements by working with operations and functional teams.
• Helping the onshore team test performance implications for a production environment.
• Working with offshore development teams on the design, implementation, and support of applications.
• Proposing technical solutions to process issues with onshore and onsite operations teams.
• Providing technical and application-related production support.
• Solving complex technical problems.
• Thinking in terms of object-oriented and application design patterns to solve complex software queries.
• Foreseeing and supervising any challenges faced by software developers.
• Spending a large amount of time coding and working with team members to satisfy customer needs.