AI Forward Deployment Engineer

EXL

Client-facing AI Forward Deployment Engineer embedding with enterprise customers to deploy AI models and workflows. Focusing on practical application, building, coding, and troubleshooting solutions.

Posted 6/5/2026full-timeNew York • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAWSAzureCloudJavaPythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

This role is client-facing, hands-on technical role that embeds with enterprise customers to deploy AI models and agentic workflows into production environments.
They bridge the gap between the EXLdata.AI platform team focusing practical application, building, coding, and troubleshooting solutions to solve complex business problems while providing feedback to improve the core AI platform.

Requirements

What you’ll need

Master’s degree in Computer Science, Computer Engineering, Data Science, Analytics, Mathematics, or a related technical field
Strong programming skills in one or more languages such as Python, Java, or Scala
Foundational knowledge of machine learning, artificial intelligence, and/or data engineering concepts
Exposure to building, testing, or deploying models or data pipelines through academic projects, internships, or research
Familiarity with modern AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, or similar)
Understanding of APIs, system integration, and working with structured and unstructured data
Strong problem-solving skills with the ability to translate business challenges into technical solutions
Excellent communication skills and ability to work directly with clients in a professional setting
Ability to thrive in ambiguous, fast-paced environments and quickly learn new technologies
Willingness to travel and work on-site with enterprise clients as needed
Preferred Qualifications:
Exposure to cloud platforms such as AWS, Azure, or Google Cloud
Experience with LLMs, generative AI, or agent-based workflows
Knowledge of data engineering tools (e.g., Spark, Databricks, Airflow)
Prior client-facing experience through internships, consulting projects, or research collaborations
Understanding of software development best practices (version control, CI/CD, testing)

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account EXL Website LinkedIn All Job Openings 10,000+ employees 💰 $2M Venture Round on 2015-01 Choosing a digital partner is about more than capabilities — it’s about collaboration and character. AI Forward Deployment Engineer 🔥 1 hour ago 🏢🏡 null – Hybrid ⏰ Full Time 🟡 Mid-level 🟠 Senior ⛑ DevOps & Site Reliability Engineer (SRE) Airflow AWS Azure Cloud Java Python PyTorch Scala Scikit-Learn Spark Tensorflow Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
This role is client-facing, hands-on technical role that embeds with enterprise customers to deploy AI models and agentic workflows into production environments.
They bridge the gap between the EXLdata.AI platform team focusing practical application, building, coding, and troubleshooting solutions to solve complex business problems while providing feedback to improve the core AI platform. 🎯 Requirements
Master’s degree in Computer Science, Computer Engineering, Data Science, Analytics, Mathematics, or a related technical field
Strong programming skills in one or more languages such as Python, Java, or Scala
Foundational knowledge of machine learning, artificial intelligence, and/or data engineering concepts
Exposure to building, testing, or deploying models or data pipelines through academic projects, internships, or research
Familiarity with modern AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, or similar)
Understanding of APIs, system integration, and working with structured and unstructured data
Strong problem-solving skills with the ability to translate business challenges into technical solutions
Excellent communication skills and ability to work directly with clients in a professional setting
Ability to thrive in ambiguous, fast-paced environments and quickly learn new technologies
Willingness to travel and work on-site with enterprise clients as needed
Preferred Qualifications:
Exposure to cloud platforms such as AWS, Azure, or Google Cloud
Experience with LLMs, generative AI, or agent-based workflows
Knowledge of data engineering tools (e.g., Spark, Databricks, Airflow)
Prior client-facing experience through internships, consulting projects, or research collaborations
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Hard Skills & Tools

PythonJavaScalamachine learningartificial intelligencedata engineeringAPIsdata pipelinessoftware development best practicesversion control

Soft Skills

problem-solvingcommunicationclient-facingadaptabilitylearning agility

Certifications

Master’s degree in Computer ScienceMaster’s degree in Computer EngineeringMaster’s degree in Data ScienceMaster’s degree in AnalyticsMaster’s degree in Mathematics