AI参与负责人
AI Engagement Lead
Tiger Analytics 是一家先进的分析咨询公司。我们是多家财富 100 强公司的信赖的分析合作伙伴，帮助他们从数据中创造商业价值。我们的顾问在数据科学、机器学习和人工智能领域拥有深厚的专业知识。我们的商业价值和领导力得到了包括 Forrester 和 Gartner 在内的多家市场研究机构的认可。
我们正在寻找一位 AI 项目负责人 / AI 工程小组负责人，能够将强大的客户和项目领导能力与 AI/ML 和生成式 AI 工程方面的实际技术专长相结合。该职位将涉及大约 50% 的项目管理与协调工作，以及 50% 的实际技术领导与 AI 工程工作。
职责：
- 从发现和解决方案定义到开发、部署和生产，主导 AI/GenAI 项目。
- 作为客户和高级利益相关者的首要技术和交付接口。
- 理解业务目标，并将其转化为 AI/ML 解决方案需求和可操作的工程计划。
- 负责项目规划、优先级排序、时间表、里程碑、风险、依赖关系和整体交付。
- 协调 AI 工程师、数据科学家、数据工程师、产品经理和客户团队。
- 进行定期的客户讨论、状态评审、技术演示和解决方案会议。
- 主动识别交付风险、技术挑战、资源限制和依赖关系，并推动解决。
- 设计、开发和部署 AI/ML 和生成式 AI 解决方案用于企业用例。
- 主导 LLM 驱动的应用程序、RAG 系统、AI 代理和代理工作流的实际开发。
- 设计和实现端到端 AI 应用架构，包括：LLM 集成、提示工程、RAG 管道、嵌入和向量数据库、工具/函数调用、代理编排、评估和监控。
- 使用 LangChain、LangGraph、LlamaIndex、Semantic Kernel 或类似技术框架。
- 集成基础模型和 LLM 平台，如 OpenAI、Azure OpenAI、Anthropic Claude、Amazon Bedrock、Gemini 或开源模型。
- 使用 Python、FastAPI、Docker、Kubernetes 和云平台开发生产级 AI 服务和 API。
- 设计检索管道，包括文档处理、分块、嵌入生成、向量搜索、混合检索和重新排序。
要求
- 10+ 年
查看英文原文
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for an AI Engagement Lead / AI Engineering Pod Lead who can combine strong client and project leadership with hands-on expertise in AI/ML and Generative AI engineering. The role will involve approximately 50% engagement/project management and coordination and 50% hands-on technical leadership and AI engineering.
Responsibilities:
- Lead AI/GenAI engagements from discovery and solution definition through development, deployment, and production.
- Serve as the primary technical and delivery interface for clients and senior stakeholders.
- Understand business objectives and translate them into AI/ML solution requirements and actionable engineering plans.
- Own project planning, prioritization, timelines, milestones, risks, dependencies, and overall delivery.
- Coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams.
- Conduct regular client discussions, status reviews, technical walkthroughs, and solutioning sessions.
- Proactively identify delivery risks, technical challenges, resource constraints, and dependencies and drive them toward resolution.
- Architect, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases.
- Lead hands-on development of LLM-powered applications, RAG systems, AI agents, and agentic workflows.
- Design and implement end-to-end AI application architectures, including: LLM integration, Prompt engineering, RAG pipelines, Embeddings and vector databases, Tool/function calling, Agent orchestration, Evaluation and monitoring
- Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies.
- Integrate foundation models and LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models.
- Develop production-grade AI services and APIs using technologies such as Python, FastAPI, Docker, Kubernetes, and cloud platforms.
- Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking.
Requirements
- 10+ years of experience in software engineering, AI/ML engineering, data science, or a related technical field.
- Strong hands-on experience building and deploying AI/ML or Generative AI solutions.
- Proven experience leading technical teams or AI engineering pods while remaining hands-on.
- Strong proficiency in Python and experience developing production-grade applications.
- Strong understanding of LLMs, Generative AI, NLP, RAG, and AI agents.
- Experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.
- Experience working with LLM APIs/foundation models such as OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source LLMs.
- Experience with vector databases and semantic search.
- Experience designing and deploying cloud-based AI solutions on AWS, Azure, or GCP.
- Strong understanding of APIs, microservices, Docker, CI/CD, and production deployment.
- Experience with AI evaluation, monitoring, guardrails, and responsible AI is highly desirable.
- Strong client-facing communication and stakeholder management skills.
- Demonstrated ability to translate ambiguous business problems into practical technical solutions.
- Master's in Business Analytics or equivalent work experience.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Originally posted on Himalayas