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Generative AI Engineer || Remote || Permanent Fulltime
• *Role AI Engineer • *Location Frederick, MD/Remote • *Permanent Fulltime • *Job description We are seeking an AI Engineer specializing in Generative AI and Agentic AI systems. This role focuses on designing, developing, and operationalizing intelligent AI agents, Large Language Model (LLM)-based applications, Retrieval-Augmented Generation (RAG) systems, and autonomous multi-agent workflows. • *Key Responsibilities • *GenAI Development & • LLM Engineering • Build and deploy LLM-based applications leveraging frameworks like LangChain. • Develop RAG pipelines using vector databases for enterprise knowledge retrieval. • Develop data pipelines to create structured and unstructured datasets for LLM and agent workflows. • Optimize prompts, system instructions, and memory architectures for robust, domain-specific reasoning. • Evaluate model performance—accuracy, hallucination mitigation, latency, and safety compliance. • *2. Agentic AI Design & • Autonomous Workflow Engineering • Implement agentic systems capable of planning, reasoning, tool usage, and multi-step decision-making. • Build multi-agent ecosystems (task agents, planning agents, critic agents, evaluation agents) to automate complex workflows. • Integrate agents with APIs, enterprise systems, and external tools to create end-to-end autonomous solutions. • Ensure agent alignment with Responsible AI principles—traceability, guardrails, human oversight. • *3. AI Systems Integration & • Deployment • Build scalable microservices and APIs for GenAI and agentic components. • Deploy models and agents using Azure ML or Kubernetes-based stacks. • 4. Collaboration & • Influence • Engage with business and product stakeholders to convert ambiguous use cases into technical solutions. • Support internal capability building—AI best practices, prompt engineering, GenAI safety, and evaluation frameworks. • *Required Skills & • Qualifications • Strong hands-on expertise in Python, LLM frameworks, and ML/DL libraries (Transformers, PyTorch, TensorFlow, scikit-learn). • Experience with API development, microservices, Docker, and Kubernetes. • Experience building RAG systems with vector databases and embeddings. • Experience with agentic frameworks or building custom autonomous agents. • Strong understanding of LLM safety, hallucination mitigation, and evaluation techniques. • Cloud proficiency in Azure (or any other hyperscalers - AWS, GCP etc) Apply tot his job Apply To this Job
