ROLE - Senior AI Engineer Contract Remote Mandatory Skill :Agentic AI; Generative AI; LLMs; LangChain Key -Must-Have Skills for Screening Python 3.11+ | LLM/GenAI | RAG | LangGraph/LangChain/LlamaIndex/Semantic Kernel/AutoGen/Bedrock Agents | LLM Evaluation | Production AI Deployment & Support | Cloud Services/APIs | AI Observability | Enterprise Security/Compliance Most important screening point: The candidate should have actually deployed an enterprise-grade GenAI/LLM application to production and supported it post-launch. POC-only GenAI experience would not meet the stated requirement. Job Description: We are seeking a Senior AI Engineer to design, build, deploy, and operate enterprise-grade Large Language Model (LLM) applications supporting business processes within a regulated financial services environment. The ideal candidate will have hands-on experience taking Generative AI solutions from design through production deployment and providing ongoing production support. This role requires deep expertise in LLM orchestration, RAG, AI evaluation, Python, cloud services, observability, and production-grade AI engineering. ________________________________________

Key Responsibilities

Design and implement multi-step LLM pipelines, including: o LLM orchestration o Structured output generation o Tool/function calling o Error handling, retry, and fallback logic Develop and maintain Retrieval-Augmented Generation (RAG) solutions, including: o Indexing strategies o Embedding model selection o Retrieval quality optimization Build and maintain LLM evaluation frameworks and golden datasets to measure accuracy, consistency, and regression risk before production releases. Establish and enforce quality gates for model, prompt, and configuration changes. Implement observability for non-deterministic AI applications, including: o Tracing o Structured logging o Quality monitoring o Cost monitoring Manage cost and latency performance of production AI workloads against defined budgets. Partner with Product, Business, Risk, Compliance, and Security teams to translate business requirements into technical solutions and support review/approval processes. Participate in code reviews, architectural decisions, and technical documentation. Provide ongoing production support for deployed AI applications, including incident response, root-cause analysis, regression management, and remediation. Mentor junior engineers and contribute to engineering standards and best practices. _