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Senior Llm Engineer Jobs in Delaware (NOW HIRING)

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Senior Llm Engineer information

What is a senior LLM engineer?

Senior LLM (Large Language Model) Engineers are experienced professionals who design, build, optimize, and maintain advanced language models like GPT, BERT, or similar AI systems. They work on tasks such as model training, fine-tuning, deployment, and troubleshooting, often collaborating with data scientists and software engineers. Their expertise includes deep learning frameworks, natural language processing, and software engineering best practices. Senior LLM Engineers also play a key role in ensuring the ethical and efficient use of AI models in production systems.

What are some common challenges senior LLM engineers face when deploying large language models in production environments?

Senior LLM Engineers often encounter challenges related to scaling models efficiently, managing latency, and ensuring model outputs are safe and reliable. Deploying large language models requires careful optimization to balance performance with computational costs, as well as robust monitoring to detect and mitigate issues like bias or hallucination in outputs. Collaboration with cross-functional teams, including data scientists, product managers, and DevOps, is key to addressing these challenges and ensuring successful model deployment and maintenance.

What are the key skills and qualifications needed to thrive as a senior LLM engineer, and why are they important?

To thrive as a Senior LLM Engineer, you need deep expertise in machine learning, natural language processing, and advanced programming skills, typically supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as PyTorch, TensorFlow, Hugging Face Transformers, and cloud platforms, along with experience in deploying large-scale language models, is crucial. Strong problem-solving, collaboration, and communication skills set top performers apart in leading cross-functional AI initiatives. These abilities are vital for developing, optimizing, and scaling cutting-edge language models that drive innovation and business value.

What is the difference between Senior Llm Engineer vs Machine Learning Engineer?

AspectSenior Llm EngineerMachine Learning Engineer
CredentialsAdvanced degrees in CS, NLP, or AI; experience with LLMsDegrees in CS, Data Science, or AI; strong programming skills
Work EnvironmentFocus on NLP, language models, and large-scale data processingBroader ML tasks, including data modeling, algorithms, and deployment
Industry UsagePrimarily in AI/NLP-focused companies, research labs

Senior Llm Engineers specialize in large language models and NLP-specific tasks, often requiring advanced NLP knowledge and experience with LLMs. Machine Learning Engineers have a broader scope, working on various ML models and applications across industries. While both roles require strong technical skills, Senior Llm Engineers focus more on language-specific AI, whereas Machine Learning Engineers handle diverse ML projects.

What are the most commonly searched types of Llm Engineer jobs in Delaware?

The most popular types of Llm Engineer jobs in Delaware are:

What are popular job titles related to Senior Llm Engineer jobs in Delaware?

For Senior Llm Engineer jobs in Delaware, the most frequently searched job titles are:

What cities in Delaware are hiring for Senior Llm Engineer jobs?

Cities in Delaware with the most Senior Llm Engineer job openings:

Infographic showing various Senior Llm Engineer job openings in Delaware as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Senior Python Full Stack Engineer - Agentic AI

Whiz Global LLC

Wilmington, DE • On-site

Other

Posted 23 days ago


Job description

Senior Python Full Stack Engineer – Agentic AI

Location: Wilmington, DE
Duration: Contract
Work Model: Hybrid/Onsite as required
Experience: 7+ YearsJob Overview

We are seeking a Senior Python Full Stack Engineer with Agentic AI experience to join the CCB Digital – Connected Banking team. The engineer will work on modern SaaS platforms that are customer-facing and integrate with internal enterprise systems.

The team is actively building AI-powered agents to solve business use cases and improve software development and platform capabilities. The ideal candidate is a strong hands-on software engineer who can contribute to architecture and design discussions, perform code reviews, and develop scalable, production-quality applications.

This is an individual contributor role, not a people-management position.

Key Responsibilities
  • Design, develop, test, and maintain scalable full-stack applications using Python.

  • Build and integrate AI agents and Agentic AI capabilities into enterprise applications.

  • Work with technologies such as MCP (Model Context Protocol), Google ADK, and other AI-agent frameworks/tools.

  • Develop applications and services that integrate with AI agents and LLM-based solutions.

  • Participate in architecture, technical design, and code review discussions.

  • Develop scalable REST APIs and microservices.

  • Build cloud-native applications using AWS and containerized environments.

  • Develop and maintain applications deployed on Kubernetes/Docker platforms.

  • Work with Kafka/event streaming technologies for asynchronous and distributed systems.

  • Design and implement solutions using NoSQL databases.

  • Implement and maintain CI/CD pipelines and automated deployment processes.

  • Write comprehensive unit, integration, and automated tests.

  • Monitor applications and troubleshoot production issues using tools such as Splunk and Dynatrace.

  • Implement application monitoring, alerting, logging, and observability capabilities.

  • Apply AI-assisted development and code optimization techniques to improve developer productivity and accelerate delivery.

  • Collaborate with architects, product owners, developers, and other engineering teams in an Agile environment.

  • Ensure solutions meet enterprise standards for security, scalability, reliability, and performance.

Required Skills & Qualifications
  • 7+ years of professional software engineering experience.

  • Strong hands-on experience with Python development.

  • Strong experience in full-stack software development.

  • Experience building REST APIs, microservices, and cloud-native applications.

  • Hands-on experience with Agentic AI / AI Agents / Generative AI.

  • Experience with one or more of:

    • MCP (Model Context Protocol)

    • Google ADK

    • AI Agent frameworks

    • LLM integrations

    • Applications designed to interact with AI agents

  • Strong experience with AWS is preferred.

  • Experience with Kubernetes and Docker/containerization.

  • Experience with Kafka or other streaming/event-driven technologies.

  • Experience with NoSQL databases such as DynamoDB, MongoDB, Cassandra, or similar.

  • Strong understanding of CI/CD and DevOps practices.

  • Experience with automated testing and unit testing frameworks.

  • Experience with application monitoring and observability tools such as Splunk, Dynatrace, or similar.

  • Strong understanding of software design, development best practices, and scalable architecture.

  • Experience participating in code reviews and technical design discussions.

  • Strong problem-solving and communication skills.

Preferred Qualifications
  • Experience with AWS cloud services and cloud-native architecture.

  • Experience developing event-driven and distributed systems.

  • Experience with LLM-based application development and AI-powered business solutions.

  • Experience using AI coding assistants/tools for code optimization and developer productivity.

  • Experience with enterprise SaaS platforms.

  • Experience working in large-scale financial services or banking environments.

  • Experience with Agile/Scrum development methodologies.

Ideal Candidate Profile

The ideal candidate is a Senior-level hands-on engineer who combines strong Python/full-stack development skills with modern cloud and AI expertise. Candidates should be comfortable working independently, reviewing code, contributing to technical design decisions, and building production-ready applications involving AI Agents and Agentic AI.

Key Technologies:
Python | Agentic AI | AI Agents | MCP | Google ADK | AWS | Kubernetes | Docker | Kafka | NoSQL | CI/CD | REST APIs | Splunk | Dynatrace | Automated Testing