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Forward Deployed Engineer - LLM/Gen AI

Evnek Technologies Pvt Ltd
Location: Posted on: 15 July 2026
Remote

Job Role: Forward Deployed Engineer - LLM/Gen AI Experience: 5-10yrs Location: Bengaluru (Remote) Notice Period: Immediate or max 15days preferred T echnical 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 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

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