Forward Deployed Engineer - LLM/Gen AI

Job Role: Forward Deployed Engineer - LLM/Gen AI

Experience:

5-10yrs Location: Bengaluru (Remote) Notice Period: Immediate or max 15days preferred Technical

Skills

Required Solid understanding of data platforms — data lakes, pipelines, transformation, and how data flows from source to AI model Working knowledge of Generative AI, LLMs, and RAG pipelines — enough to scope deliverables and review outputs critically Ability to read and understand data models, architecture diagrams, and API specs — you don't write production code but understand what's being built Cloud platforms — AWS and/or Azure — data and AI services at a conceptual and delivery level Familiarity with Snowflake, Databricks, or equivalent — enough for informed conversations with data engineers

Experience

using AI platforms and tools to rapidly prototype and demonstrate solutions to clients Delivery & Client

Skills

Required 6–10 years in AI/data product delivery, technical consulting, or engineering — not pure product management Proven ability to run discovery independently — without a senior consultant holding your hand Strong client-facing presence — comfortable presenting to senior business and technology stakeholders

Experience

writing SOWs, project proposals, or technical specifications that get signed off by clients Track record of owning delivery outcomes — accountable for the result, not just managing tasks

Experience

in consulting, professional services, or embedded delivery model strongly preferred Ability to manage multiple workstreams simultaneously in a fast-paced pod environment

Requirements

Requirements

Key

Skills

• Cloud Architecture (AWS/Azure/GCP)
• AI/ML, Generative AI, and Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG) and AI Agents
• API Design and Enterprise Integrations
• Data Pipelines, Data Lakehouse, and Data Mesh
• MLOps, CI/CD, Model Registry, and Model Observability
• Security, Governance, and Cost Optimization

Solid understanding of data platforms — data lakes, pipelines, transformation, and how data flows from source to AI model Working knowledge of Generative AI, LLMs, and RAG pipelines — enough to scope deliverables and review outputs critically Ability to read and understand data models, architecture diagrams, and API specs — you don't write production code but understand what's being built Cloud platforms — AWS and/or Azure — data and AI services at a conceptual and delivery level Familiarity with Snowflake, Databricks, or equivalent — enough for informed conversations with data engineers

Experience

using AI platforms and tools to rapidly prototype and demonstrate solutions to clients Delivery & Client

Skills

Required 6–10 years in AI/data product delivery, technical consulting, or engineering — not pure product management Proven ability to run discovery independently — without a senior consultant holding your hand Strong client-facing presence — comfortable presenting to senior business and technology stakeholders

Experience

writing SOWs, project proposals, or technical specifications that get signed off by clients Track record of owning delivery outcomes — accountable for the result, not just managing tasks

Experience

in consulting, professional services, or embedded delivery model strongly preferred Ability to manage multiple workstreams simultaneously in a fast-paced pod environment

Requirements

Requirements

Key

Skills

• Cloud Architecture (AWS/Azure/GCP)
• AI/ML, Generative AI, and Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG) and AI Agents
• API Design and Enterprise Integrations
• Data Pipelines, Data Lakehouse, and Data Mesh
• MLOps, CI/CD, Model Registry, and Model Observability
• Security, Governance, and Cost Optimiz