Senior Forward Deployed Engineer – AI

IBM; Paramus (NJ); Remote; USD 150,000 - 210,000; Full time

Job summary

IBM Consulting is seeking a Forward Deployed Engineer - AI to partner with clients across industries, transforming complex business challenges into production-ready GenAI and agentic AI solutions. You will combine software engineering, data science, and advanced analytics to rapidly prototype, deploy, and scale AI capabilities that deliver measurable business value.

You will translate business needs into technical roadmaps, design end-to-end GenAI applications using LangGraph, CrewAI, and

Qualifications

• 8–12+ years of experience delivering production AI solutions.
• Strong Python and SQL skills with GenAI and agentic AI experience.
• Hands-on building GenAI apps with LLMs, RAG, and agentic AI.
• Experience designing agentic AI workflows with LangChain, LangGraph, CrewAI.
• Experience with ML and data processing using scikit-learn, PyTorch, Pandas, or Spark.
• Experience deploying AI solutions via APIs and cloud platforms; Git, Docker, Kubernetes.
• Experience with major cloud AI platforms (AWS Bedrock, Azure Foundry, Google Vertex AI).
• Strong client-facing skills and ability to translate business needs into technical solutions.

Responsibilities

• Solve Client Challenges: Identify opportunities, define AI use cases, and establish success metrics.
• Build and Deploy AI Solutions: Develop GenAI, RAG, and agentic AI apps using LangGraph, CrewAI, and hyperscaler platforms.
• Engineer Agentic and GenAI Systems: Design LLM-powered agents, tool use and orchestration, prompt engineering, and evaluation frameworks.
• 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, demonstrate outcomes, and enable client adoption.

Skills

AI/ML experience

Python & SQL

GenAI & agentic AI

Embeddings & vector DB

LLM workflows & orchestration

ML tools (scikit-learn, PyTorch, Pandа

APIs & Cloud platforms

Cloud AI platforms

Client-facing skills

Bachelor’s degree

Education

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

Master’s or PhD (preferred)

Tools

Git

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

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

Required Qualifications

• 8-12+ 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

Preferred Qualifications

• 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.