> Markdown version of [/jobs/ext/100495-sr-ai-forward-deployment-engineer](https://www.wearedevelopers.com/jobs/ext/100495-sr-ai-forward-deployment-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. AI Forward Deployment Engineer - **Company:** EXL SERVICE - **Location:** United States - **Experience:** Expert - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Computer Programming, Computer Engineering, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Software Tools, Tensorflow, Systems Integration, Unstructured Data, Google Cloud, Pytorch, Large Language Models, Apache Spark, Generative AI, Scikit Learn, Information Technology, Machine Learning Operations, Software Version Control, Data Pipelines, Databricks - **Published:** May 31, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e564bb9027464bed ## About the Role Do you have experience in Systems integration?, Do you have a Master's degree?, * 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 technologiesWillingness 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) ## Description Responsibilities: 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [The Software Engineer 2030: From Coder To AI Orchestrator? - Patrick Schnell](https://www.wearedevelopers.com/videos/1825-the-software-engineer-2030-from-coder-to-ai-orchestrator-patrick-schnell) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)