About the Role Engineer scalable platforms and services supporting AI and agent-based workloads. Key Responsibilities • Develop AI services and APIs • Integrate COTS AI/agent platforms • Support deployment pipelines • Optimize performance and cost • Ensure reliability of AI services in production Work Areas & Outcomes – Platform engineering, AI services, MLOps Qualifications Optimal qualification for success on the job is: • 5-8 years. Role Proficiencies: For successful execution of the job, the candidate should possess: Capability & Skill Expectations – • Hands-on data science skills applied to GenAI use cases, including model fine-tuning, prompt optimization, testing, and evaluation. • Experience with LLMs, embeddings, retrieval, and agent-based architectures Platform & Engineering Exposure – • Experience applying COTS model-development and agent-development platforms to business use cases. • Ability to integrate APIs, orchestration frameworks, vector databases, and enterprise data sources. Observability & Evaluation Expectations – Exposure to observability and evaluation for AI/agent-based apps, including prompt/version tracking, quality evaluation, latency and cost monitoring, hallucination analysis, and human-in-the-loop feedback.