
1001 - 5000 employees
Founded 2011
đ„ Healthcare
đŠ Logistics
đŁ Marketing
Healthcare âą Logistics âą Marketing
Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.
đ„ 15 minutes ago
đ California â Remote
â° Full Time
đ Senior
đ€ Artificial Intelligence
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1001 - 5000 employees
Founded 2011
đ„ Healthcare
đŠ Logistics
đŁ Marketing
Healthcare âą Logistics âą Marketing
Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.
âą Lead AI/GenAI engagements from discovery and solution definition through development, deployment, and production âą Serve as the primary technical and delivery interface for clients and senior stakeholders âą Translate business objectives into AI/ML solution requirements and actionable engineering plans âą Own project planning, prioritization, timelines, milestones, risks, dependencies, and overall delivery âą Coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams âą Conduct regular client discussions, status reviews, technical walkthroughs, and solutioning sessions âą Identify delivery risks, technical challenges, resource constraints, and dependencies and drive them toward resolution âą Architect, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases âą Lead hands-on development of LLM-powered applications, RAG systems, AI agents, and agentic workflows âą 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 âą Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies âą Integrate foundation models and LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models âą Develop production-grade AI services and APIs using Python, FastAPI, Docker, Kubernetes, and cloud platforms âą Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking
âą 10+ years of experience in software engineering, AI/ML engineering, data science, or a related technical field âą Strong hands-on experience building and deploying AI/ML or Generative AI solutions âą Proven experience leading technical teams or AI engineering pods while remaining hands-on âą Strong proficiency in Python and experience developing production-grade applications âą Strong understanding of LLMs, Generative AI, NLP, RAG, and AI agents âą Experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent âą Experience working with LLM APIs/foundation models such as OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source LLMs âą Experience with vector databases and semantic search âą Experience designing and deploying cloud-based AI solutions on AWS, Azure, or GCP âą Strong understanding of APIs, microservices, Docker, CI/CD, and production deployment âą Experience with AI evaluation, monitoring, guardrails, and responsible AI is highly desirable âą Strong client-facing communication and stakeholder management skills âą Demonstrated ability to translate ambiguous business problems into practical technical solutions âą Master's in Business Analytics or equivalent work experience
âą Significant career development opportunities âą Small, fast-growing, challenging and entrepreneurial environment âą High degree of individual responsibility âą Equal employment opportunities 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
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