Manager

• Project Planning: Develop comprehensive project plans for life and annuity projects, including scope, timelines, resources, and budgets. Define project objectives and deliverables. Developing and maintaining the project plans using the project work breakdown structures, product backlogs, sprint backlogs, project and program charters, scope definition, schedules, resource requirements.
• Product Knowledge: Leverage expertise in life insurance and annuity products to guide project requirements, design, and implementation.
• Resource Management: Manages cross-functional team members and subject matter experts, including definition of objectives, oversight of execution and evaluation of performance.
• Stakeholder Communication: Serve as the primary point of contact for stakeholders, including internal teams, clients, and vendors. Provide regular updates on project status and address any issues.
• Regulatory Compliance: Ensure all projects adhere to industry regulations, standards, and company policies.
• Risk Management: Identify potential risks specific to life and annuity projects and develop strategies to mitigate them.
• Budget Management: Monitor and manage project budgets, ensuring cost-effectiveness and alignment with financial goals.
• Quality Assurance: Oversee the quality of project deliverables to ensure they meet industry standards and client expectations.
• Documentation: Maintain detailed project documentation, including plans, reports, and change requests.
• Team Leadership: Lead and motivate project teams, ensuring alignment with project goals and fostering a collaborative work environment. Provides thought leadership and delivers business insights to identify and resolve complex issues critical to their clients’ success.
• Problem Solving: Address and resolve project-related issues and challenges in a timely and effective manner.
• As part of their expanded responsibilities, the Manager will lead the implementation of AI initiatives aligned with business objectives. This includes identifying opportunities for AI-driven automation and analytics within ongoing projects, collaborating with data science and engineering teams, and ensuring AI solutions are integrated seamlessly into existing platforms and workflows such as LifePRO, LDS, portals, and operations systems. By embedding AI delivery into project execution, the PM plays a key role in accelerating digital transformation, improving efficiency, and delivering measurable business value.

Senior Delivery Manager

Auditor

• Conducts insurance policy audits for Worker’s Compensation, Auto and General Liability policies.
• Scheduling appointments with the insured to be audited.
• Travel on an average of 4 days per week within your assigned territory to meet with the insured.
• Obtain necessary documentation for insurance company client audits while adhering to customer requirements and quality standards.

Experienced Premium Insurance Field 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

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

Software Engineer

• Develop, maintain, and enhance SAS programs, macros, and scripts.
• Perform data extraction, transformation, and loading (ETL) activities.
• Analyze large datasets and generate reports for business insights.
• Design and optimize SAS data models and workflows.
• Validate and troubleshoot SAS jobs and production issues.
• Collaborate with cross-functional teams to gather business requirements.
• Create automated reports and dashboards.
• Ensure data accuracy, integrity, and compliance with company standards.
• Participate in code reviews and documentation activities.
• Support deployment and maintenance of SAS applications.
• Participate in migration of SAS workloads, ETL jobs, and batch processes from SAS GRID to SAS Viya.
• Analyze existing SAS GRID environments, ETL workflows, scheduling dependencies, and data pipelines.
• Convert and validate SAS programs, macros, and ETL processes for SAS Viya compatibility.
• Support migration of SAS Enterprise Guide projects, batch scripts, and shared libraries.
• Ensure migrated jobs execute efficiently within the SAS Viya compute environment.
• Identify compatibility issues and recommend remediation approaches.
• **Quality Assurance & Validation**
• Perform code validation and reconciliation between SAS GRID and SAS Viya outputs.
• Conduct unit testing, system testing, and parallel run validations.
• Troubleshoot migration and ETL-related issues.
• Ensure data quality, accuracy, and process integrity throughout migration activities.
• **Stakeholder & Client Engagement**
• Collaborate with business users, data teams, infrastructure teams, and architects.
• Provide regular updates on migration progress and issue resolution.
• Support client discussions and technical walkthroughs as needed.

SAS Developer

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.

Business Analyst – IC

• Review and analyze patient medical records to extract relevant clinical information in line with defined guidelines and criteria.
• Apply clinical knowledge and judgment to accurately interpret diagnoses, treatments, and patient history.
• Summarize key medical insights in a clear, concise, and structured format for further review or decision-making.
• Ensure compliance with clinical standards, documentation protocols, and data confidentiality requirements.
• Collaborate with internal teams to clarify clinical details and maintain high-quality output within defined timelines.

Assistant Manager – Physician Reviewer

Data Analyst

• design, developing, and deploying data-driven solutions across the retail lending lifecycle
• work closely with cross-functional teams to uncover opportunities, build models, optimize processes, and enhance decision-making frameworks through modern data science and business intelligence capabilities

Recruitment

• Play a key role in identifying, attracting, and hiring high-quality talent
• Manage and deliver end-to-end hiring processes
• Develop effective sourcing strategies and assess candidate suitability
• Proactively build and maintain a high-quality talent pipeline
• Collaborate with hiring managers to understand talent needs
• Develop and execute recruitment strategies
• Utilise various sourcing methods to attract qualified candidates
• Review resumes and evaluate candidates against job requirements
• Champion diversity and inclusion efforts within the recruitment process
• Cultivate and maintain relationships with candidates
• Partner with HR to align recruitment efforts

Talent Acquisition Specialist

Risk

• Own and manage centralized intake process for MarTech requests, ensuring completeness, proper categorization, and routing.
• Serve as the central coordination point for MarTech intake and issue escalations, including logging, triaging, prioritizing, and routing requests and issues to Product, Architecture, or vendor teams, while ensuring visibility, tracking, and timely resolution.
• Track and report on intake SLAs, request status, and prioritization outcomes.
• Coordinate user access requests across MarTech platforms, ensuring alignment with governance and role-based permissions.
• Support quarterly user access recertification processes in partnership with IT and Security teams.
• Maintain governance logs, including tracking of segments, journeys, and sandbox usage across a multi-tenant environment.
• Assist in enforcing platform standards, naming conventions, and usage guidelines across internal & external users.
• Coordinate and support governance forums, intake triage meetings, and cross-functional working sessions.
• Document decisions, action items, and maintain centralized documentation repositories.
• Track platform adoption, usage trends, and open issues to support operational reporting.
• Assist with UAT coordination, release tracking, and cross-team communication.

Product Coordinator – MarTech Platforms, Governance

AI Engineer

• Design and implement agentic AI systems (single and multi-agent) with tool use, memory, and fallback mechanisms.
• Build production-grade agents using frameworks like LangGraph, AutoGen, CrewAI, or custom LLM orchestration layers.
• Implement agent reasoning loops including planning, tool selection, execution, observation, and re-planning with safety guardrails.
• Develop prompt and context engineering strategies for reliable, grounded LLM outputs.
• Design agent orchestration workflows include task routing, parallel execution, state management, retries, and human-in-the-loop escalation.
• Build evaluation frameworks for LLMs and agents including automated testing, adversarial testing, and performance benchmarking.
• Implement retrieval and grounding using vector databases, embeddings, and knowledge graphs for contextual accuracy.
• Ensure observability of agent systems by tracing LLM calls, tool usage, and decision paths using monitoring tools.
• Apply security and governance controls including prompt injection defense, access control, and safe tool execution.
• Optimize agent systems for latency, cost, and scalability in production environments.
• Build CI/CD pipelines for agent workflows including versioning, testing, and controlled deployments.
• Integrate agents with enterprise systems and APIs to automate end-to-end business workflows.
• Design feedback loops using production traces and evaluation signals to continuously improve agent performance.
• Experience with Model Context Protocol (MCP) systems to design database connections, integrate APIs, and enable secure tool orchestration for AI agents.
• Hands-on experience in fine-tuning LLMs for domain-specific applications using LoRA, PEFT, QLoRA, RLHF, instruction tuning, and other parameter-efficient adaptation techniques.
• Stay current with emerging agentic AI frameworks, research, and best practices for production deployment.