Gen AI Engineer

Experteer Overview In this Data Science Consultant 2 role at Infosys Topaz, you will develop data preparation pipelines and ready data for advanced modeling. You’ll build and refine models, including forecasting and LLM-based solutions, and deploy scalable, production-ready analytics. You’ll guide teammates, ensure governance and quality, and drive data-driven insights for business challenges. This position offers hands-on work with cutting-edge AI tech and opportunities to influence transformation at scale. Compensation / Benefits * Develop data preparation tasks and identify data patterns * Ensure data readiness for advanced modeling * Develop and optimize models for complex use cases (forecasting, LLM-based) and deploy production-ready solutions * Test, optimize, and guide best practices across the team * Design and develop predictive models and data-driven analyses * Build, evaluate, deploy, and standardize analytics code; contribute to knowledge management * Leverage SAS and R/Python to create reusable AI customizations across ML and deep learning * Define analytics problems and execute visualization, analysis, and predictive modeling under guidance * Maintain models, implement improvements for accuracy and reliability * Apply governance controls to mitigate risks and ensure compliance * Analyze performance trends and document discrepancies for escalation * Maintain documentation standards and participate in knowledge transfer * Engage with stakeholders to refine requirements and guide model implementation * Apply quality measurement framework at task level; validate deployment success * Develop scripts/templates for repeated deployment tasks * Contribute to analytic solutions, IP assets, and training initiatives * Contribute to thought leadership through papers and proofs of concepts * Deliver analytics training and contribute to content creation * Support business planning with data-driven insights Tasks * Python proficiency and hands-on experience building GenAI apps with LangChain, Lang Graph, Llama Index or similar orchestration frameworks * Experience with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic or similar LLM platforms; enterprise API/database integration * Production API and microservice development with FastAPI, Docker, Kubernetes; solid software engineering fundamentals (design, testing, CI/CD, Git) * LLMOps practices including observability, tracing, evaluation, guardrails, cost governance, model safety * Code reviews, technical decision making, collaboration with product/platform teams Key requirements * Medical/Dental/Vision/Life Insurance * 401(k) plan and contributions * Paid holidays plus Paid Time Off * Disability insurance * Health and Dependent Care Reimbursement Accounts * Insurance (Accident, Critical Illness, Hospital Indemnity, Legal)

create to create reusable AI customizations across ML and deep learning * Define analytics problems and execute visualization, analysis, and predictive modeling under guidance * Maintain models, implement improvements for accuracy and reliability * Apply governance controls to mitigate risks and ensure compliance * Analyze performance trends and document discrepancies for escalation * Maintain documentation standards and participate in knowledge transfer * Engage with stakeholders to refine requirements and guide model implementation * Apply quality measurement framework at task level; validate deployment success * Develop scripts/templates for repeated deployment tasks * Contribute to analytic solutions, IP assets, and training initiatives * Contribute to thought leadership through papers and proofs of concepts * Deliver analytics training and contribute to content creation * Support business planning with data-driven insights Tasks * Python proficiency and hands-on experience building GenAI apps with LangChain, Lang Graph, Llama Index or similar orchestration frameworks * Experience with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic or similar LLM platforms; enterprise API/database integration * Production API and microservice development with FastAPI, Docker, Kubernetes; solid software engineering fundamentals (design, testing, CI/CD, Git) * LLMOps practices including observability, tracing, evaluation, guardrails, cost governance, model safety * Code reviews, technical decision making, collaboration with product/platform teams Key requirements * Medical/Dental/Vision/Life Insurance * 401(k) plan and contributions * Paid holidays plus Paid Time Off * Disability insurance * Health and Dependent Care Reimbursement Accounts * Insurance (Accident, Critical Illness, Hospital Indemnity, Legal)