Title: AI Cloud Innovator
Location: Chennai, Bangalore, Hyderabad
Who we are
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.
Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.
We are a Great Place to Work-Certified™ (2022-25), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine.
About the Role
We are seeking a visionary AI Cloud Innovator with a strong background in consulting and engineering. This role is dedicated to accelerating our capabilities in the most emerging AI fields, specifically Generative AI, Large Language Models (LLMs), and Agentic AI systems.
This is a high-visibility, execution-focused role where your primary function is to rapidly ingest, test, and articulate our Point of View (POV) on new cloud-native AI products and services from our core partners: Google Cloud Platform (GCP), AWS, Microsoft Azure, Databricks, and Snowflake.
You will be the engine of innovation, developing tangible, demoable Proofs of Concept (POCs) and technical solutions that solidify our position as a leading, continuously learning AI partner.
Key Responsibilities: The Innovation Engine
- Emerging Technology Mastery: Be the first to experiment with and master the latest Generative AI models, vector databases, multi-modal capabilities, and agentic frameworks (e.g., LangChain, LlamaIndex, function calling, RAG) across all major cloud providers.
- Rapid POV & POC Development: Design, build, and deploy quick-turnaround, compelling POCs and technical demonstrations that showcase our expertise and the immediate business value of these new technologies.
- Partner Alignment & Positioning: Work closely with Alliance/Partner teams to create unique technical narratives and solutions tailored to joint go-to-market efforts with GCP, AWS, Microsoft, Databricks, and Snowflake.
- Technical Content Leadership: Develop clear, structured technical content—including code artifacts, solution templates, and concise executive summaries (POVs)—that can be used by client-facing teams, marketing, and in partner forums.
- Multi-Cloud Engineering: Ensure all POCs are built leveraging multi-cloud capabilities, demonstrating fluency and best practices in integrating AI services across the specified platforms (AWS SageMaker/Bedrock, Azure AI Services/OpenAI, GCP Vertex AI, Databricks Mosaic AI, Snowflake Cortex).
- Knowledge Transfer: Conduct internal workshops and training sessions to disseminate cutting-edge knowledge, enabling other consulting and delivery teams to scale successful POCs into production-ready solutions.
What You Bring:
- Deep AI/ML Expertise (5+ years): Hands-on experience across traditional Machine Learning (MLOps, feature engineering) AND a demonstrated, keen interest or experience in Generative AI/LLMs.
- Cloud Native Fluency (Mandatory): Hands-on experience designing and deploying solutions on at least two of the following: GCP, AWS, Azure. Familiarity with AI/ML services on Databricks and Snowflake is a significant advantage.
- Agility & Prototyping: A proven ability to move rapidly from concept to code artifact, thrive in unstructured environments, and deliver high-quality, demo-ready prototypes quickly.
- Generative AI Toolkit: Practical experience with key GenAI components such as prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning (LoRA, QLoRA), and building multi-step AI agents.
- Communication & Influence: Exceptional ability to distill complex, highly technical concepts (e.g., transformer architectures, agent loop design) into clear, business-relevant language for clients and partners.
- Consulting Mindset: A strong focus on understanding the "why" behind business problems and proactively identifying where the newest AI innovations can deliver disproportionate value.