Gen AI Engineer

Experteer Overview In this role you’ll develop data preparation and modeling solutions to support complex business needs. You will build, evaluate, and deploy predictive models including LLM-based applications, ensuring production readiness and governance. You’ll collaborate with stakeholders, share knowledge, and drive improvements in accuracy, reliability, and performance. This position offers exposure to cutting-edge GenAI technologies and opportunities to shape scalable analytics solutions within a dynamic team. Compensation / Benefits * Develop data preparation tasks and identify data patterns * Prepare data for advanced modeling and ensure readiness * Create and refine models for complex use cases including forecasting and LLM-based solutions * Test, optimize, and deploy models in production-ready, scalable solutions * Design and develop predictive models and data-driven analyses * Build, evaluate, deploy and standardize analytics code; contribute to knowledge sharing * Leverage SAS and R/Python to create reusable customizations for ML and non-ML tasks * Define analytics problems; execute visualization, analysis, and predictive modeling under guidance * Maintain models and implement improvements for accuracy and reliability * Apply governance controls to mitigate risks and ensure compliance * Analyze performance trends; document discrepancies for escalation * Maintain documentation standards and participate in knowledge transfer * Engage with stakeholders to refine requirements and guide model implementation * Deploy analytics tools and validate deployment success * Contribute to IP assets, training initiatives, and thought leadership * Deliver analytics training and create content * Support business planning with data-driven insights Tasks * Python proficiency and hands-on building of enterprise GenAI apps with orchestration frameworks (Lang Chain, Lang Graph, Llama Index) * Experience with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic or similar LLM platforms; integration with enterprise APIs and knowledge repositories * Building production APIs and microservices (FastAPI, Docker, Kubernetes); software engineering fundamentals (design, testing, CI/CD, Git) * Experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor) * LLMOps practices (observability, tracing, evaluation, guardrails, cost governance, model safety) * Code reviews and cross-team collaboration to drive technical decisions Key requirements * Medical/Dental/Vision insurance * Disability insurance * Health and Dependent Care Reimbursement Accounts * 401(k) plan * Paid holidays and Paid Time Off

to SAS and R/Python to create reusable customizations for ML and non-ML tasks * Define analytics problems; execute visualization, analysis, and predictive modeling under guidance * Maintain models and implement improvements for accuracy and reliability * Apply governance controls to mitigate risks and ensure compliance * Analyze performance trends; document discrepancies for escalation * Maintain documentation standards and participate in knowledge transfer * Engage with stakeholders to refine requirements and guide model implementation * Deploy analytics tools and validate deployment success * Contribute to IP assets, training initiatives, and thought leadership * Deliver analytics training and create content * Support business planning with data-driven insights Tasks * Python proficiency and hands-on building of enterprise GenAI apps with orchestration frameworks (Lang Chain, Lang Graph, Llama Index) * Experience with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic or similar LLM aaaaaaaa to integration with enterprise APIs and knowledge repositories * Building production APIs and microservices (FastAPI, Docker, Kubernetes); software engineering fundamentals (design, testing, CI/CD, Git) * Experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor) * LLMOps practices (observability, tracing, evaluation, guardrails, cost governance, model safety) * Code reviews and cross-team collaboration to drive technical decisions Key requirements * Medical/Dental/Vision insurance * Disability insurance * Health and Dependent Care Reimbursement Accounts * 401(k) plan * Paid holidays and Paid Time Off