Senior Lead, Full-stack Forward Deployed Engineer
Who We Are
The Role
Key Responsibilities
Full-Stack Engineering & MVP Delivery
- Architect, build, and scale modern frontend interfaces using 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, Node.js, or TypeScript to connect enterprise systems with advanced language models.
- Rapidly prototype and ship functional, production-ready MVPs within weeks in a highly iterative, agile environment.
- Optimize application performance, ensuring fast database query execution, reliable data flows, and highly responsive rendering speeds.
Agentic AI & Knowledge Systems Architecture
- Design, build, and deploy multi-agent orchestration frameworks using LangChain, AutoGen, CrewAI, LangGraph, or Semantic Kernel that communicate, self-correct, and execute complex business 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, context window limitations, and system-level security.
Customer Engagement & Solution Integrity
- Partner directly with enterprise customers to understand business challenges, translating complex requirements into high-quality, fit-for-purpose technical architectures.
- Lead end-to-end technical delivery from scoping and prototyping to production deployment, prioritizing sustainable, long-term outcomes over temporary fixes.
- Bridge engineering rigor with business value, communicating technical trade-offs and solution impact confidently to both technical teams and executive stakeholders.
Field Intelligence & Platform Contribution
- Deploy and manage secure, containerized full-stack applications using Docker and Kubernetes across major cloud hyper-scalers including AWS, Azure, and GCP.
- Systematically capture deployment learnings, document best practices, and share insights to continuously enhance Kyndryl's core AI platforms and frameworks.
- Collaborate daily with local engineering leads to improve deployment pipelines and cultivate an open, knowledge-sharing engineering culture.
Kyndryl currently does not require employees to be fully vaccinated against COVID-19, however, if you are hired to work at a client, customer, or partner location, you may be required to show proof of vaccination to align with their respective COVID-19 vaccination policies. Those who believe they are eligible may apply for a medical or religious accommodation prior to the start of employment.
Who You Are
Required Skills and Experience
- 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
- 4+ years of professional software engineering experience with strong proficiency in Python and JavaScript/TypeScript backend development.
- Hands-on experience building and deploying applications using modern AI frameworks and agentic orchestrators (such as LangChain, AutoGen, CrewAI, LangGraph, or Semantic Kernel) in production.
- Experience designing, building, and maintaining modern frontend applications (React, Angular, or Vue), particularly handling streaming data or real-time query responses.
- Practical experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases (such as Pinecone, Milvus, Qdrant, or Chroma).
- Experience building and deploying containerized applications using Docker and Kubernetes across major cloud hyper-scalers (AWS, Azure, or GCP).
- Solid grasp of the software delivery lifecycle, version control using Git and GitHub, CI/CD pipelines, and data engineering tools (such as Pandas, Spark, and SQL/NoSQL databases like PostgreSQL).
- Experience partnering with enterprise customers to translate business requirements into technical solutions and troubleshooting system performance, scalability, and reliability.
- Degree-level qualification in Computer Science, Software Engineering, Informatics, Data Science, or a related technical field (or equivalent practical work experience).
Preferred Skills and Experience
- Experience working with AI/ML frameworks such as TensorFlow or PyTorch, as well as open-source AI ecosystems and libraries including Hugging Face.
- Experience with LLM infrastructure tools such as LiteLLM gateways, prompt tracing platforms (such as Langfuse), system prompt tuning, model fine-tuning, and vector search caching strategies (such as Redis).
- Experience using workflow managers (such as Temporal), messaging queues, or streaming platforms like Kafka or RabbitMQ.
- T-shaped technical profile with deep expertise in full-stack AI engineering combined with broad domain understanding across cloud platforms and enterprise consulting.
- Active technical contributions or feedback provided to core AI platforms, open-source repositories, or internal frameworks.
- Flexibility and willingness to travel and work on customer premises as required.
- Active professional certifications in major cloud hyper-scalers (AWS, Azure, or GCP) or AI-specific development pathways.
- Advanced degree (Master's or higher) in Computer Science, Software Engineering, Data Science, or a closely related technical discipline.
Equal Opportunity Employer
Being You
What You Can Expect
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Not included in the source posting: benefits.
Skills
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