Senior Forward Deployed AI Engineer

Job not on LinkedIn

🕒 August 4

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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TechTorch

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

TechTorch is an AI-native B2B company that provides revenue operations and digital transformation solutions for enterprises and private-equity–backed portfolio companies. Their Beacon platform and AI agents automate quote-to-cash, CRM modernization (Salesforce, HubSpot, Dynamics), CPQ, data integration, analytics, billing/subscriptions, and other revenue workflows to accelerate growth, reduce errors, and deliver rapid, measurable value.

📋 Description

• Own work end to end, from discovery and solution shaping through system design, build, and production deployment • Design and build data foundations, including data models, schema design, dimensional modeling, ETL/ELT pipelines, and slowly changing dimensions • Build full-stack applications using Python/FastAPI services and Next.js frontends • Use AI coding agents such as Claude Code or equivalent as a primary build accelerator • Design and build AI capabilities including RAG pipelines, agentic workflows, and LLM-in-the-loop processing • Compose AI capabilities via MCP servers, Skills, and Plugins • Orchestrate pipelines and automation using Airflow, Dagster/Prefect, Celery, or Temporal • Own CI/CD and cloud deployments on AWS and Azure • Translate ambiguous client requirements into clear designs and communicate trade-offs to technical and business audiences • Contribute reusable accelerators and technical assets to the Data Practice

🎯 Requirements

• Genuine production depth across data engineering and full-stack development • Data modeling and schema design, including dimensional modeling, normalization trade-offs, and EDW/warehouse schema design • Hands-on production ETL/ELT experience across batch and incremental loads • Knowledge of slowly changing dimensions and change-data handling patterns • Experience with dbt, including modular SQL transformations, tests, documentation, and incremental strategies • Advanced SQL and in-depth experience with at least one modern data platform such as Snowflake or Databricks • Data quality practices including testing, validation, and lineage • 5+ years with Python as a primary language • FastAPI experience, including async REST API design, dependency injection, and testing • Modern frontend experience, ideally Next.js, including component architecture, SSR, state management, and UX • PostgreSQL schema design, query optimization, and indexing • System design and ability to architect services, boundaries, trade-offs, and scale from a blank page • Daily experience using an agentic coding tool such as Claude Code, Cursor, or comparable tools • Ability to own CI/CD and cloud deployments on AWS or Azure without heavy support • Comfortable with client-facing delivery and translating between business and engineering • Customer-first mindset • End-to-end ownership from discovery through production • Nice-to-have qualifications include Salesforce/NetSuite commercial data fluency, LangGraph or comparable agentic AI, RAG engineering, consulting or forward-deployed engineering experience, workflow orchestration, streaming data, vector databases, experiment tracking, open-source contributions, and multi-cloud or hybrid cloud exposure

🏖️ Benefits

• Fully remote • Semi-annual team offsites, with in-person gatherings at least twice a year • High-autonomy, high-ownership work across real client problems • Access to the full modern data and AI stack • Room to grow toward data architecture, platform leadership, or AI engineering depth