Forward Deployed Engineer, AI

IBM

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: CharlotteRaleighBostonAtlantaDallasHoustonAustinWashingtonCambridgeChicagoDetroitNew York
Posted: 2 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $191k

$135k $240k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $152,543–$229,425.

Based on 240 similar postings.

Employer

About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 242 open roles on FindRole.

Listed pay typically runs $180,812–$215,000 across 9 roles with salary data.

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At a glance

TL;DR · Forward Deployed Engineer, AI

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As a Forward Deployed Engineer – AI, you will work directly with clients to transform complex business challenges into production-ready AI solutions. You will partner with business and technical teams to identify opportunities, define use cases, and establish success metrics. Your daily responsibilities include developing end-to-end GenAI, RAG, and agentic AI applications while integrating solutions with enterprise systems and APIs. You will design LLM-powered agents using LangGraph, CrewAI, and hyperscaler cloud AI platforms like AWS, Google, and Azure. Key technical tasks involve prompt engineering, evaluation frameworks, and applying MLOps or LLMOps practices for observability and safety. You will prepare structured and unstructured data to ensure reliability while turning successful solutions into reusable assets to solve specific technical and business problems for diverse client environments.

What does a Forward Deployed Engineer earn?

Median $208800 from 49 postings across 21 companies.

See salary data

Skills

GenAI RAG Agentic AI LangGraph CrewAI MLOps LLMOps AWS Cloud Azure Vertex AI Azure AI Foundry Amazon Bedrock APIs Data Engineering Observability

What you'll do

Identify AI use cases and establish success metrics with client business and technical teams.
Develop end-to-end GenAI, RAG, and agentic AI applications using LangGraph, CrewAI, and cloud platforms.
Design and implement LLM-powered agents, prompt engineering, and evaluation frameworks.
Apply guardrails, observability, and testing to ensure AI accuracy, safety, and reliability.
Prepare structured and unstructured data and integrate AI solutions with enterprise systems and APIs.
Apply MLOps/LLMOps practices to monitor and scale AI solutions for production environments.
Present insights and demonstrate outcomes to support client adoption of new AI solutions.
Convert successful client solutions into reusable assets for future engagements.

What we're looking for

Develop end-to-end GenAI, RAG, and agentic AI applications using tools like LangGraph, CrewAI, and hyperscaler cloud AI platforms.
Design and implement LLM-powered agents, tool use, prompt engineering, and evaluation frameworks.
Apply guardrails, observability, and testing to ensure AI accuracy, safety, and reliability.
Prepare structured and unstructured data and integrate AI solutions with enterprise systems, APIs, and data platforms.
Apply MLOps/LLMOps, testing, monitoring, and responsible AI practices to ensure production-ready solutions.
Partner with business and technical teams to identify opportunities, define AI use cases, and establish success metrics.
Present insights, demonstrate outcomes, and support client adoption of AI solutions.

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