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Professional Llm Developer Jobs in Kentucky (NOW HIRING)

$220 - $240/hr

Senior AI Engineer, AI Platform & LLM Systems Compensation: Senior: ~$220k-$240k base | Significant ... This team is rethinking how highly skilled professionals interact with complex data, documentation ...

New

$95 - $135/hr

Implement AI-assisted data techniques: embeddings, vector search, LLM-augmented query and reporting ... Required Qualifications * 5+ years of professional experience with Microsoft SQL Server (2016 and ...

New

$106 - $183/hr

Vendor assessment and risk management along with secure LLM integrations.**Your Qualifications:****Required:*** **Experience:** 8+ years of professional software engineering experience, with at least ...

New

$150 - $190/hr

We're seeking creative, collaborative, and self-driven professionals across all areas of our ... developers to work through complex implementation challenges, including those involving LLM ...

New

$120 - $180/hr

... LLM-powered systems. * Help grow the engineering team by participating in hiring and technical ... Qualifications * 5+ years of professional software engineering experience with demonstrated ...

New

$118 - $222/hr

Partners closely with cyber security professionals, platform and operations engineers to ensure ... LLM-powered or agentic applications, including Eval design • Strong prompt, context, and tool ...

New

$115 - $145/hr

Design, build, and maintain LLM-powered and agentic workflows using tools like LangGraph and ... RemoteLevel: 2-5 years of professional software development experienceBase Salary Range: $115K ...

New

$41.50 - $55/hr

... LLM-based agents, autonomous decision-making loops). * Design and implement advanced integrations ... Professional Experience: * Minimum of 5+ years of experience in technology delivery, with at least ...

$156 - $187/hr

... LLM systems to support the client's Commerce AI team. This role sits at the intersection of ... QUALIFICATIONS * 8+ years of professional software engineering experience. * 3+ years of dedicated ...

New

... engineer. As Lead, Offensive Security (AI & Tooling), you will own the in-house AI agent platform ... of LLM-driven penetration-testing agents, built for production use by a professional red team.

... engineer. As Lead, Offensive Security (AI & Tooling), you will own the in-house AI agent platform ... of LLM-driven penetration-testing agents, built for production use by a professional red team.

... engineer. As Lead, Offensive Security (AI & Tooling), you will own the in-house AI agent platform ... of LLM-driven penetration-testing agents, built for production use by a professional red team.

... engineer. As Lead, Offensive Security (AI & Tooling), you will own the in-house AI agent platform ... of LLM-driven penetration-testing agents, built for production use by a professional red team.

Develop and fine-tune LLM applications for data enrichment, content generation, and data ... Collaborate with data engineering teams on MLOps and automation pipeline development * Document ...

$240 - $315/hr

Our team is a quickly growing group of committed researchers, engineers, policy experts, and ... Maintain strong knowledge of the latest developments in LLM capabilities and implementation ...

New

$106 - $160/hr

As a Solutions Integration Engineer at Samsara, you will be an integral member of the Professional ... Proficient in leveraging LLM-based tools like Cursor and Codex and MCPs for code generation, prompt ...

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Professional Llm Developer information

What is a professional LLM developer?

Professional LLM Developers are software engineers or specialists who design, build, and optimize applications and systems that leverage large language models (LLMs) like GPT-4, Claude, or similar AI models. Their work often involves integrating LLMs into products, fine-tuning models for specific tasks, ensuring safe and ethical AI use, and improving performance. They may also create tools and frameworks that facilitate the deployment and scaling of LLM-powered applications. Their expertise combines software development, machine learning, and natural language processing.

What is the difference between Professional Llm Developer vs Machine Learning Engineer?

AspectProfessional Llm DeveloperMachine Learning Engineer
CredentialsTypically requires advanced degrees in AI, NLP, or related fields; certifications in AI/MLOften holds degrees in computer science, data science, or engineering; certifications in ML frameworks
Work EnvironmentFocuses on developing and fine-tuning large language models, often in research or specialized AI teamsDesigns, builds, and deploys ML models across various applications, in industry or tech companies
Industry UsagePrimarily in AI research, NLP, and companies developing LLM-based productsUsed across tech, finance, healthcare, and other sectors for predictive modeling and automation

While both roles involve AI and machine learning, a Professional Llm Developer specializes in large language models and NLP, whereas a Machine Learning Engineer works on a broader range of ML applications and models across industries.

What are the key skills and qualifications needed to thrive as a professional LLM developer?

To thrive as a Professional LLM Developer, you need expertise in machine learning, natural language processing, and strong programming skills in languages like Python, often supported by a degree in computer science or related fields. Familiarity with deep learning frameworks (such as PyTorch or TensorFlow), experience with large language model architectures, and knowledge of cloud platforms are typically required, along with certifications like TensorFlow Developer or AWS Certified Machine Learning. Strong problem-solving abilities, teamwork, and effective communication distinguish top performers in this role. These skills ensure the development, fine-tuning, and deployment of robust LLM solutions that meet business and technical needs.

What are some common challenges faced by professional LLM developers when deploying large language models in production environments?

Professional LLM Developers often encounter challenges such as optimizing model performance to balance accuracy with computational efficiency, managing latency for real-time applications, and ensuring data privacy and security. Additionally, integrating LLMs with existing systems and maintaining model versioning can be complex. Collaboration with cross-functional teams, such as data engineers and product managers, is essential to address these challenges and ensure the successful deployment and ongoing maintenance of LLM-driven solutions.

What are the most commonly searched types of Llm Developer jobs in Kentucky?

The most popular types of Llm Developer jobs in Kentucky are:

What are popular job titles related to Professional Llm Developer jobs in Kentucky?

For Professional Llm Developer jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Professional Llm Developer jobs in Kentucky look for?

The top searched job categories for Professional Llm Developer jobs in Kentucky are:

What cities in Kentucky are hiring for Professional Llm Developer jobs?

Cities in Kentucky with the most Professional Llm Developer job openings:

$220 - $240/hr

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Job description

Senior AI Engineer, AI Platform & LLM Systems

Compensation: Senior: ~$220k–$240k base | Significant equity

Location: San Francisco, hybrid

Employment Type: Full-time

A fast-scaling, well-funded B2B SaaS company building AI-native software for complex, high-value professional workflows.

This team is rethinking how highly skilled professionals interact with complex data, documentation, and knowledge-heavy processes. Following significant recent funding and continued commercial growth, AI has become a central part of the company’s product and engineering strategy.

Rather than adding lightweight AI features around an existing product, the engineering organization is investing heavily in the underlying platform required to make production AI reliable: evaluation, ingestion, observability, retrieval, orchestration, and the infrastructure supporting increasingly capable AI workflows.

What You’ll Do
  • Build and scale core AI platform capabilities across evals, ingestion, observability, retrieval, and AI/ML infrastructure
  • Own AI systems end-to-end, taking ideas from prototype through to reliable production deployments
  • Design and improve RAG pipelines, embedding workflows, prompt systems, retrieval strategies, and model interaction patterns
  • Develop infrastructure for evaluating, monitoring, versioning, and improving LLM-powered systems
  • Build tooling around AI workflow orchestration, quality control, experimentation, and production reliability
  • Work with complex, domain-specific datasets to improve retrieval and model performance
  • Partner closely with product, design, engineering, and subject-matter experts to turn sophisticated workflows into usable AI products
  • Help establish technical patterns and engineering standards for applied AI across the wider organization
What You’ll Bring
  • Strong software engineering experience across areas such as backend engineering, distributed systems, infrastructure, developer platforms, or ML systems
  • Strong hands-on Python engineering skills
  • Experience shipping AI or ML systems into production rather than working exclusively on prototypes or research
  • Practical experience with one or more of LLMs, RAG, NLP, AI agents, model evaluation, observability, data ingestion, or AI/ML infrastructure
  • Strong understanding of software architecture, system design, reliability, and production engineering
  • Ability to operate comfortably across both AI-specific problems and traditional software engineering challenges
  • A high bar for engineering quality, including the ability to critically review AI-generated code rather than treating generated output as production-ready
  • A pragmatic builder mentality and an appetite for high ownership in a fast-moving technical environment
Tech Stack
  • Python
  • LLMs / Generative AI
  • Retrieval-Augmented Generation (RAG)
  • Embeddings & semantic retrieval
  • LLM evaluation frameworks
  • AI observability & monitoring
  • Data / document ingestion pipelines
  • Workflow orchestration
  • AI / ML infrastructure
  • Distributed backend systems
Why Join?

This is an opportunity to join at an important inflection point: the company has strong funding, an established product and customer base, and executive-level commitment to making AI a fundamental part of the platform.

You’ll have significant ownership over the infrastructure that determines whether AI systems actually work in production, from how information enters the system and is retrieved, through to how outputs are evaluated, monitored, and continuously improved.

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