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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 job categories do people searching Senior Llm Engineer jobs in Delaware look for?

The top searched job categories for Senior Llm Engineer jobs in Delaware are:

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

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

Senior Llm Engineer jobs near you
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.

AI Engineer - Sr Lead Software Engineer

JPMorgan Chase & Co

Wilmington, DE • On-site

Full-time

Medical, Retirement

Posted 5 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

77th of 175 rated banks

Job description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the AI/ML Data Platforms team, you will be a key member of an agile team responsible for enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will drive meaningful business impact through hands-on engineering leadership, applying deep technical expertise and structured problem-solving to address complex challenges across multiple technologies and applications. In this role, you will help design and deliver agentic AI platforms and large language model (LLM)-enabled services for enterprise use cases. You will contribute to architecture and engineering decisions, build cloud-native services on AWS, and improve system quality through strong evaluation, observability, and operational excellence practices. You will also raise engineering standards through high-quality code reviews, clear documentation, and effective collaboration across teams.

Job responsibilities

  • Provide technical guidance and direction to business and engineering teams by partnering with external teams to align on priorities, unblock delivery, and drive successful engineering outcomes.
  • Develop secure, high-quality production code and lead code reviews; review, debug, and improve code written by others to raise overall engineering quality.
  • Drive architecture and design decisions that influence product design, application functionality, and technical operations (including SDLC practices).
  • Serve as a subject matter expert in one or more focus areas, helping teams make sound technical trade-offs and resolve complex problems.
  • Evaluate and introduce leading-edge technologies where appropriate, influencing peers and decision-makers with clear rationale and risk/benefit analysis.
  • Build and operate production-grade LLM applications, including agentic patterns and tool integrations for enterprise use cases.
  • Design and deliver cloud-native services on AWS using containers and serverless architectures, with strong attention to scalability and operational resilience.
  • Implement retrieval-augmented generation (RAG) solutions, including embeddings, semantic search, and practical context engineering to improve answer quality and control.
  • Build reliable service APIs and integrations with a focus on security, performance, and maintainability.

  • Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. 

  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale. 

Required Qualifications, Capabilities, and Skills: 

  • Formal training or certification on software engineering concepts and 5+ years applied experience 
  • Strong Python engineering skills; experience with PyTorch or TensorFlow 
  • Expertise working with Vector storage systems and designing memory for Agents 
  • Expertise developing long running agents that run autonomously using tools, skills and human in the loop 
  • Proven experience deploying LLM-backed services to production (APIs, microservices) 
  • Deep MLOps experience, including CI/CD, monitoring, incident response, and model governance 
  • Cloud-native AI deployment experience (AWS or Azure), with cost and performance optimization 
  • Demonstrated commitment to responsible AI practices and operational excellence 
  • Strong communication and collaboration skills, working across product, risk, legal, and compliance teams 
  • Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data. 
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.  

Preferred Qualifications, Capabilities, and Skills: 

  • Experience with fine-tuning, adapters, or custom evaluation frameworks.
  • Background operating AI systems in regulated environments (finance, healthcare, etc.).
  • Experience with prompt engineering and LLM orchestration.
  • Knowledge of safety filters, audit logging, and explainability in production systems.
  • Experience mentoring senior engineers and leading architecture discussions.
  • Demonstrated ability to influence technical roadmaps and priorities.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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