Contact Center Forward Deployed Engineer – AI

IBM; Paramus (NJ); Remote; USD 130,000 - 180,000; Full time

Job summary

IBM Consulting is seeking a Forward Deployed Engineer - AI to work with clients across industries transforming complex challenges into production-ready AI solutions. You will prototype, deploy, and scale GenAI, RAG, and agentic AI applications using LangGraph, CrewAI, and hyperscaler cloud platforms.

The role emphasizes client-facing collaboration, data engineering, and scalable MLOps practices. The position can be performed from anywhere in the United States, offering opportunities to impact

Qualifications

• 5–7+ years delivering production AI solutions in AI/ML, data science, or software engineering.
• Strong Python and SQL skills; hands-on GenAI and agentic AI apps with LLMs, RAG, and multi‑step workflows.
• Hands-on GenAI with embeddings and vector databases (e.g., Milvus, Elasticsearch, pgvector, Pinecone).
• Experience designing agentic AI workflows using LangChain/LangGraph, CrewAI, AutoGen.
• Experience with scikit-learn, PyTorch, Pandas, or Spark.
• Experience deploying AI via REST/FastAPI, cloud AI platforms, Docker, and Kubernetes.
• Practical experience with at least one cloud AI platform (AWS Bedrock, Azure Foundry, Google Vertex AI).
• Strong client-facing communication; translate business needs into technical solutions.
• Bachelor’s degree in CS/Engineering/Data Science or related field.

Responsibilities

• Solve Client Challenges: identify AI use cases and success metrics with business and technical teams.
• Build and Deploy AI Solutions: end-to-end GenAI, RAG, and agentic AI apps using LangGraph, CrewAI, cloud platforms.
• Engineer Agentic and GenAI Systems: design LLM-powered agents, tool use, orchestration, prompts, and evaluation.
• Data Engineering and Integrations: prepare data and integrate AI with enterprise systems and APIs.
• Scale and Operationalize AI: apply MLOps/LLMOps, testing, monitoring, and responsible AI practices.
• Drive Business Impact: present insights, enable client adoption, create reusable assets.

Skills

Python

SQL

GenAI

LLMs

RAG

LangChain/LangGraph

CrewAI

APIs (REST/FastAPI)

Cloud platforms (AWS/Azure/Google)

Docker/Kubernetes

PyTorch/Pandas/Spark

Education

Bachelor’s degree in Computer Science, Engineering, Data Science

Tools

LangGraph

CrewAI

AWS Bedrock

Google Vertex AI

Azure AI Foundry

Vertex AI

Bedrock

Milvus

Elasticsearch

pgvector

Pinecone

Docker

Kubernetes

Job description

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your role and responsibilities

As a Forward Deployed Engineer - AI, you will work directly with clients to transform complex business challenges into production-ready AI solutions. Combining software engineering, data science, GenAI, agentic AI, and advanced analytics, you will rapidly prototype, deploy, and scale solutions that deliver measurable business value.

Your primary responsibilities will include:

• Solve Client Challenges: Partner with business and technical teams to identify opportunities, define AI use cases, and establish success metrics.

• Build and Deploy AI Solutions: Develop end-to-end GenAI, RAG, and agentic AI applications using tools such as LangGraph, CrewAI, and hyperscaler cloud AI platforms (e.g., AWS, Google, Azure).

• Engineer Agentic and GenAI Systems: Design and implement LLM-powered agents, tool use and orchestration, prompt and context engineering, and evaluation frameworks using platforms such as LangGraph, CrewAI, Vertex AI, Azure AI Foundry, or Amazon Bedrock. Apply guardrails, observability, and testing to ensure accuracy, safety, and reliability.

• Data Engineering and Integrations: Prepare structured and unstructured data and integrate AI solutions with enterprise systems, APIs, and data platforms.

• Scale and Operationalize AI: Apply MLOps/LLMOps, testing, monitoring, and responsible AI practices to ensure solutions are reliable, secure, and production-ready.

• Drive Business Impact: Present insights, demonstrate outcomes, support client adoption, and turn successful solutions into reusable assets for future engagements.

This job can be performed from anywhere in the US.

Required technical and professional expertise

• 5-7+ years of experience in AI/ML, data science, or software engineering, delivering production AI solutions.

• Strong Python and SQL skills, with hands‑on experience building GenAI and agentic AI applications, including LLMs, RAG, and multi‑step workflows using tools such as LangChain, LangGraph, or CrewAI.

• Hands‑on experience building GenAI applications with large language models, including RAG, prompt and context engineering, embeddings and vector databases (e.g., Milvus, Elasticsearch, pgvector, Pinecone), and LLM evaluation.

• Experience designing and building agentic AI workflows using frameworks such as LangChain/LangGraph, CrewAI, AutoGen, including tool calling and multi‑step orchestration.

• Experience with machine learning and data processing using tools such as scikit‑learn, PyTorch, Pandas, or Spark.

• Experience integrating and deploying AI solutions using APIs (REST/FastAPI), cloud AI platforms (AWS Bedrock, Azure AI, or Google Vertex AI), and tools such as Git, Docker, or Kubernetes.

• Experience with at least one major cloud AI platform (AWS Bedrock, Azure AI Foundry, or Google Vertex AI).

• Strong client‑facing skills, with the ability to translate business challenges into technical solutions and communicate with technical and non‑technical audiences.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.

Preferred technical and professional experience

• Master’s or PhD in a technical or quantitative field.

• Experience with LLM fine‑tuning, AI evaluation and governance,

• Industry experience in high tech, electronics or manufacturing.

• Background in forward deployed engineering, solutions engineering, or client‑facing consulting.

• Front‑end development experience (e.g., React or Streamlit), cloud/AI certifications, or open‑source AI contributions.

IBM is committed to creating a diverse environment and is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.