Fullstack Forward Deployed Engineer

Kyndryl•Dallas, TX

1d•$115,080 - $262,320•Hybrid

About The Position

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. As a Fullstack Forward Deployed Engineer, you are the technical force that customers ask for by name. You will step into an ultra-fast, high-autonomy "builder’s paradise" to turn ambitious architectural blueprints into real-world software platforms, designing and deploying responsive modern frontends, developing robust backend pipelines, and orchestrating advanced multi-agent workflows that solve complex enterprise challenges. Operating from our physical Lab in Frisco, Texas, you will work in an iterative, rapid prototyping environment where we ship functional MVPs in weeks, not months. While your day-to-day focus is pure hands-on development—making use of modern retrieval-augmented generation (RAG) models, managing LLM API performance, and launching production-ready systems onto major cloud hyper-scalers—you will also embed directly with enterprise clients for high-value co-creation, helping them navigate ambiguity and taking accountability for real outcomes in production environments.

Requirements

Based in the Dallas-Fort Worth metroplex (or ready to relocate immediately) with a hybrid schedule of 3 days onsite per week at the Frisco, TX Agentic AI Lab.
Hands-on experience building applications using modern frameworks and orchestrators (e.g., LangChain, AutoGen, or CrewAI) in production.
4+ years of professional software engineering experience with strong proficiency in Python and JavaScript/TypeScript backend development.
Experience designing and maintaining modern frontend applications (React, Angular, or Vue), particularly handling streaming data or real-time query responses.
Practical understanding of Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., Pinecone, Milvus, Qdrant, Chroma).
Experience deploying containerized applications (Docker, Kubernetes) to AWS, Azure, or GCP.
Strong proficiency with SQL (PostgreSQL, etc.) and NoSQL databases.
Deep familiarity with Git/GitHub, CI/CD pipelines, and software delivery best practices.

Nice To Haves

Experience with LLM infrastructure tools such as LiteLLM gateways, prompt tracing platforms (e.g., Langfuse), or workflow managers (e.g., Temporal).
Familiarity with system prompt tuning, model fine-tuning, and vector search caching strategies (e.g., Redis).
Experience using messaging queues or streaming platforms like Kafka or RabbitMQ.
Active professional certifications in major cloud hyper-scalers (AWS, Azure, GCP) or AI-specific development pathways.
Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field (or equivalent practical work experience).

Responsibilities

Build and scale modern frontend interfaces (React, Angular, or Vue) designed to handle dynamic generative UI elements and real-time streaming outputs.
Develop robust backend APIs and data pipelines using Python or Node.js to connect client systems with advanced language models.
Rapidly prototype and ship functional, production-ready MVPs within weeks in a highly iterative, agile lab environment.
Optimize application performance, ensuring fast database query execution and highly responsive rendering speeds.
Design, build, and deploy multi-agent orchestration frameworks (using LangChain, AutoGen, or CrewAI) that communicate, self-correct, and execute complex workflows.
Configure and optimize Retrieval-Augmented Generation (RAG) architectures, integrating both structured and unstructured data sources into unified vector engines.
Manage LLM integration challenges including API call optimization, token latencies, prompt routing, and context window limitations.
Deploy and manage secure, containerized full-stack applications using Docker and Kubernetes across major cloud hyper-scalers (AWS, Azure, or GCP).
Collaborate daily with local engineering leads to continuously improve the physical Lab's deployment pipelines and core platforms.
Participate in cross-functional stand-ups and share knowledge openly across Slack and Teams to cultivate a highly collaborative team environment.