Teams at Tiger Analytics

Lead hands-on architecture, development, deployment, and optimization of enterprise GenAI, RAG, Agentic AI, and Neo4j Knowledge Graph solutions. Build data pipelines, APIs, microservices, and cloud-native AI infrastructure; rapidly deliver customer POCs and production systems. Serve as the primary technical interface for enterprise clients, troubleshooting performance, scalability, reliability, and cost issues while providing technical consulting.

Lead strategic programs comprising multiple concurrent projects, aligning goals with organizational objectives. Manage program schedules, dependencies, budgets, risks, milestones, and performance metrics. Remove technical and operational blockers, coordinate cross-functional teams, escalate issues, and facilitate status meetings, executive dashboards, and program reviews. The role requires strong project and program management experience, SDLC and Agile methodology knowledge, and the ability to drive consensus across engineering teams.

Deploys, integrates, and scales enterprise generative AI solutions in customer cloud environments. Responsibilities include architecting GCP and Vertex AI infrastructure, deploying and optimizing LLMs, building RAG data and vector search pipelines, managing GPU/TPU workloads on GKE, automating infrastructure with Terraform, and advising clients on AI safety, prompt engineering, hallucinations, and inference costs. The role also collaborates with research and platform teams and requires travel to client sites.