Senior Agentic AI Developer at Kyndryl to build autonomous AI systems for complex tasks. Collaborating to integrate LLMs and achieve real - world business outcomes.
CU
Hybrid AI Engineer – Mission Innovation Lab
Posted last month
About the role
- AI Engineer translating cutting-edge AI concepts into mission-scale solutions for the warfighting community. Collaborate with researchers and government sponsors to develop secure, reliable AI capabilities.
Responsibilities
- translate cutting-edge AI concepts into robust, mission-scale solutions for the warfighting community
- work with large-scale foundation models such as GPT and LLaMA, designing and deploying agentic workflows
- apply and advance traditional ML research and engineering across domains such as natural language processing, computer vision, time series forecasting, and other predictive analytics
- collaborate closely with senior researchers, software engineers, and government sponsors to define problem statements and iterate on experimental designs
- deliver secure, reliable AI capabilities that meet stringent mission requirements
- design, develop, and fine-tune a variety of AI models
- design autonomous agents and multi-step pipelines using LangChain, ReAct, tool-calling, or custom orchestration
- build Retrieval-Augmented Generation pipelines that combine external knowledge bases with LLMs to improve factual accuracy for warfighting applications
- implement end-to-end data pipelines, ETL processes, and back-end services (Python, C/C++, Java) that feed data to models
- create CI/CD pipelines for model training, validation, containerized deployment (Docker/Kubernetes), and security scanning
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field
- at least four years of relevant experience (or an M.S. with two years)
- Ability to obtain and maintain an active Department of War (DoW) security clearance
- Proficiency in Python and at least one compiled language (C/C++ or Java)
- Experience with REST/GraphQL APIs and containerization
- Strong grasp of ML theory (supervised, unsupervised, reinforcement learning) and evaluation metrics
- Hands-on experience fine-tuning LLMs and using frameworks such as Hugging Face Transformers, LangChain, or comparable agent tools
- Familiarity with building RAG pipelines (vector stores, dense/sparse retrievers)
- Experience applying PEFT/LoRA methods (e.g., LoRA, adapters) to large models
- Understanding of Model Context protocols for managing model state across multi-turn interactions
- Experience building evaluation frameworks, benchmarks, or data quality pipelines
- Experience with TensorFlow, PyTorch, or JAX; knowledge of data-pipeline tools (Airflow, Prefect, Ray) is a plus
- Awareness of DevSecOps practices (CI/CD, GitOps, container security scanning, model-registry concepts) is desirable
Benefits
- comprehensive medical, prescription, dental, and vision insurance
- generous retirement savings program with employer contributions
- tuition benefits
- ample paid time off and observed holidays
- life and accidental death and disability insurance
- free Pittsburgh Regional Transit bus pass
- access to Family Concierge Team for childcare needs
- fitness center access
- much more
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