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Senior Llm Engineer Jobs in Delaware (NOW HIRING)

Monitise

Lead AI Engineer

Wilmington, DE · On-site

$186K - $285K/yr

Mentor senior engineers, foster communities of practice, and promote architectural thinking ... LLM-powered applications or agents in production with platforms such as Anthropic Claude, OpenAI ...

Athena LLC

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Collaborate with senior AI engineers to prototype systems that use AI for agentic workflows ...

Athenago

AI Engineering Intern

Wilmington, DE · On-site

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Collaborate with senior AI engineers to prototype systems that use AI for agentic workflows ...

JPMorgan Chase & Co.

$120 - $170/hr

... E support within an enterprise environment. * Proven ability to lead triage calls across ... Tooling experience with ServiceNow, Splunk, Alteryx, LLM. * SQL experience would be outstanding.

JP Morgan Chase

CCB Risk Program Associate

Wilmington, DE

$57K - $57K/yr

Work closely with senior management to develop and implement ambitious, innovative modeling ... LLM prompt engineering. * Hands-on experience with LLM APIs, Python libraries like Pandas, NumPy ...

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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.

Staff Engineer -Developer Insights & AI Telemetry

Capital One

Wilmington, DE • On-site

Full-time

Re-posted just now

Key responsibilities

  • Lead the strategy, implementation, and long-term vision for the enterprise Developer Insights domain, focusing on Data Engineering, ML/AI engineering, and AI telemetry.

  • Architect and evolve the internal developer telemetry platform to handle high-volume, low-latency event data across global regions.

  • Own the deployment of advanced inference capabilities, including models that score code complexity, categorize AI use cases, and measure ROI of generative AI tools.

Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

89th of 175 rated banks

Job description

Staff Engineer -Developer Insights & AI Telemetry

As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will operate as a hands-on technical visionary, leading the strategy, implementation, and long-term vision for our enterprise Developer Insights domain, with a dedicated focus on Data Engineering strategies, ML/AI engineering, distributed AI telemetry, and AI Insights.

In this role, you will work alongside our talented team of developers, data engineers, machine learning experts, product managers, and people leaders. Our domain-driven organizational structure drives higher accountability and ownership, empowering you to bridge the gap between deep technical implementation and executive-level business value. You will champion Capital One's native, vendor-agnostic AI impact telemetry platform, scaling it into an enterprise-grade "Mission Control" layer that captures, analyzes, and optimizes human-AI collaboration for multi-disciplinary users.

If you are ready to provide thought leadership, inject high-engineering rigor into the software delivery lifecycle, and build engineering excellence across Capital One, come join us in our mission to change banking for good.

Key Responsibilities

  • Vision & Strategy: Architect the long-term enterprise roadmap for distributed AI telemetry, streaming data engineering, and automated developer insight frameworks.

  • Enterprise Scaling & Telemetry: Lead the technical evolution of our internal developer telemetry platform from a high-performance Agent Hook Architecture into a stateless, low-latency utility capable of handling billions of annual high-fidelity events across global regions.

  • ML/AI & Intelligence Layer: Spearhead the deployment of advanced inference capabilities, including LLM-as-a-Judge models, to autonomously score code complexity, categorize AI use cases (e.g., Core Logic vs. Testing), and calculate the TrueThroughput and return on investment (ROI) of generative AI tools.

  • Data Engineering & Architecture: Own the end-to-end data strategy, shifting from traditional batch reporting to real-time event-driven architectures utilizing a scalable Medallion (Bronze/Silver/Gold) data structure feeding directly into our enterprise data lake.

  • Business Metric Correlation: Partner with Bank Tech Analytics to link AI code density data and telemetry directly with core business outcomes-such as lowering Feature Lead Time (FLT) and PR cycle time-without compromising quality and risk bars.

  • Risk & Privacy Governance: Design and enforce rigorous privacy-by-design principles, implementing automated PII masking, token management, and secret filtering to guarantee a completely safe space for engineering innovation.

  • Culture & Technical Contribution: Lead through direct technical contribution-prototyping systems, evaluating build vs. buy paths, authoring code patterns, and deeply mentoring principal and senior engineers across the Developer Enablement tower.

Basic Qualifications

  • Bachelor's Degree.

  • At least 7 years of experience in software engineering, solution architecture, or enterprise architecture.

  • At least 5 years of experience with big data engineering, distributed computing, or data architecture (e.g., Spark, Kafka, Kinesis, ClickHouse, Snowflake, or cloud data warehouses).

  • At least 3 years of experience with Big Data and data streaming

  • At least 4 years of experience building and optimizing production-grade ML/AI lifecycles, pipelines, or frameworks.

  • At least 2 years of cloud computing experience (AWS, Microsoft Azure, or Google Cloud).

Preferred Qualifications

  • Master's Degree in Computer Science, Information Systems, Data Engineering, or a related engineering discipline.

  • 10+ years of professional experience coding in commonly used languages like Python, Go, Java, or TypeScript.

  • 6+ years of experience designing and managing high-throughput distributed streaming architectures or edge collection telemetry platforms (e.g., OpenTelemetry, Protobuf interception hooks).

  • 3+ years of experience in a technical leadership role directly influencing VP/SVP/Executive stakeholders on multi-million dollar technology or AI strategy initiatives.

  • Deep understanding of compliance, data privacy, and cybersecurity constraints within a highly regulated environment (BankTech), including experience co-authoring risk assessments alongside Cyber and Risk teams.

  • Proven track record of operating within a product-centric organization (Domain Category Owner/Technical Product Owner model), delivering tactical values in continuous validation cycles.

  • Experience utilizing advanced engineering metrics (DORA, SPACE, AI Telemetry, Feature Lead Time) to demonstrate how developer tool investments translate into measurable corporate velocity and efficiency gains.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $269,100 - $307,200 for Distinguished Engineer


New York, NY: $293,600 - $335,100 for Distinguished Engineer


Richmond, VA: $244,700 - $279,200 for Distinguished Engineer


Wilmington, DE: $244,700 - $279,200 for Distinguished Engineer








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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