# Tiger Analytics — AI Engagement Lead

- Generated: 2026-09-12 08:44:46 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4466343104/
- Provider: LinkedIn
- Posted: approximately 2026-09-11 01:44 PM EDT (from '19 hours ago')
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp
- Applicants: 26 applicants
- Work model/location: San Francisco, California; no remote designation in the role posting
- Compensation: Not disclosed for a non-Director/VP/Chief title
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: FAIL — 88%

## Direct-match strengths

Hands-on GenAI and AI engineering, client delivery, Python, FastAPI, AWS, LangChain/LangGraph, RAG, agents, tools, orchestration, vector search, APIs, microservices, Docker, Kubernetes, CI/CD, evaluation, monitoring, guardrails, and stakeholder leadership.

## Hard or material gaps

Hard location/work-model conflict: the posting is in San Francisco and provides no remote option, while Keith allows remote U.S. roles or Massachusetts-based roles. Compensation is also undisclosed for a non-Director/VP/Chief title. The applicant count is acceptable and the technical fit is strong, but neither overrides those hard gaps.

## Evidence map

1. 10+ years software or AI engineering (weight 3, evidence 3/3) — Twenty-nine years of software architecture plus extensive AI/ML delivery.
2. Client and project leadership (weight 3, evidence 3/3) — Direct enterprise consulting, delivery planning, executive communication, and stakeholder management.
3. Hands-on production GenAI (weight 3, evidence 3/3) — Built and operates production LLM, RAG, agent, and automation systems.
4. Python, FastAPI, APIs, Docker, Kubernetes, CI/CD (weight 3, evidence 3/3) — Direct supported production experience.
5. RAG, retrieval, embeddings, vectors, and reranking (weight 3, evidence 3/3) — Direct retrieval, PGVector, semantic search, and RAG evidence; reranking is less explicit.
6. Evaluation, monitoring, guardrails, and responsible AI (weight 2, evidence 3/3) — Direct evaluation, observability, governance, and guardrail evidence.
7. Location and work model (weight 3, evidence 0/3) — San Francisco posting with no remote designation conflicts with constraints.
8. Compensation (weight 3, evidence 0/3) — Undisclosed for a non-Director/VP/Chief title.

## Keyword diagnostic

Strong hands-on AI engagement and technical-leadership alignment; independently disqualified by San Francisco location/work model and undisclosed compensation.

## Full normalized job description

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.

## Artifact metadata

- Resume: Not generated because the fit gate returned FAIL.
- Cover letter: Not generated because the fit gate returned FAIL.
- LinkedIn note: Not generated for a FAIL role.
- Google Drive used: No