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# Senior - Forward Deployed Engineer

- **Company:** Kyndryl, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $115,080.0 - $218,520.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Computer Programming, Programming Tools, Distributed Systems, Github, Intelligence Analysis, Python (Programming Language), Knowledge-Based Systems, Machine Learning, Node.Js, Open Source Technology, Systems Development Life Cycle, Rapid Prototyping Process, Software Tools, Tensorflow, Software Engineering, Systems Integration, TypeScript, Pytorch, Multi-Agent Systems, Apache Spark, Generative AI, Pandas, AI Platforms, Kubernetes, Information Technology, HuggingFace, Virtual Agents, Software Version Control
- **Published:** September 17, 2026
- **Apply:** https://dejobs.org/x/x/3EABE9CB27664CF1806FE6F5896F8CD5/job/

## About the Role

*Programming Proficiency: Demonstrable expertise in Python, (or another modern language such as C#, Node.js or TypeScript); experience working with AI/ML frameworks like TensorFlow or PyTorch is a plus

*Software Engineering: Solid grasp of the software delivery lifecycle, version control (Git & GitHub), and data engineering tools such as Pandas and Spark

*Cloud & Distributed Systems: Experience with cloud AI platforms (AWS, Azure, Google AI) and distributed computing architectures

Preferred skills and experience

*Open-Source Ecosystems: Familiarity with community-driven AI tools and libraries, including Hugging Face and relevant repositories

*T-shaped Profile: Deep technical expertise in one or two domains, with broad understanding across AI/ML, cloud, and consulting

*Agentic AI Systems: Experience designing, building, or integrating multi-agent systems and orchestration frameworks (e.g., LangGraph, Semantic Kernel, Agent Framework, AutoGen, CrewAI), including the development of agent protocols and coordination mechanisms

*Retrieval-Augmented Generation (RAG) & Knowledge Systems: Practical knowledge of deploying RAG architectures and integrating structured and unstructured knowledge sources into AI solutions

*Performance & Security: Knowledge of system-level optimisation and security best practices for scalable AI systems

*Business Acumen: Ability to translate business requirements into technical solutions and communicate technical value to diverse stakeholders, including executive audiences

*Flexibility: Willingness to travel and work on customer premises as required

*Education: Degree-level qualification in Computer Science, Informatics, Data Science, Engineering, or a closely related discipline - or equivalent professional experience

Must be willing to work onsite West Palm Beach, FL

## Description

Your role

As a Forward Deployed Engineer (FDE), you own end to end delivery for complex AI engagements. You translate business challenges into technical solutions, lead solution design and deployment, and operate as a trusted technical partner to customers. You are accountable not just for what gets built, but for whether it works-technically, operationally, and for the people who rely on it.

You operate with significant autonomy, bring deep expertise in at least one technical domain, and confidently bridge engineering rigor with business value. You use AI assisted development tools across the full delivery lifecycle to accelerate learning, improve quality, and deliver measurable impact.

What you will do

*Customer Engagement & Solution Integrity: Partner with customers to understand business challenges and translate them into high-quality, fit-for-purpose technical solutions, prioritising the right outcome over the fastest one

*Rapid Prototyping: Build and iterate custom AI solutions tailored to customer needs, leveraging agentic AI frameworks

*Ownership, Deployment & Partnership: Own delivery end to end, from scoping to production. Work as part of the customer team to engineer and deploy production-ready solutions that drive adoption and measurable business outcomes.

*Optimization: Troubleshoot and enhance system performance, scalability, and reliability

*Field Intelligence: Systematically capture deployment learnings, document best practices, and proactively share insights to inform enhancements to Kyndryl's core platforms and frameworks

*Continuous Learning: Adapt quickly to emerging technologies and evolving customer requirements by engaging in ongoing professional development

*Platform Contribution: Actively contribute to the evolution of Kyndryl's AI platforms through feedback, code contributions, and collaboration with product teams


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