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Contract Llm Developer Jobs in Nevada (NOW HIRING)

JT4, LLC provides engineering and technical support to multiple western test ranges for the U.S ... Air Force, Space Force, and Navy under the Joint Range Technical Services Contract, better known as ...

JT4, LLC provides engineering and technical support to multiple western test ranges for the U.S ... Air Force, Space Force, and Navy under the Joint Range Technical Services Contract, better known as ...

Contract Llm Developer information

What is a contract LLM developer?

Contract LLM Developers are professionals hired on a temporary or project basis to design, develop, and implement applications using large language models (LLMs) like GPT-4. They typically work with organizations seeking to integrate advanced natural language processing (NLP) capabilities into their products or services. Contract LLM Developers are skilled in machine learning, programming languages such as Python, and have experience with AI frameworks and APIs. Their responsibilities may include fine-tuning language models, building conversational AI systems, and ensuring the ethical use of AI technologies.

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

To thrive as a Contract LLM Developer, you need strong programming skills (often in Python), a solid understanding of machine learning concepts, and experience with large language models, typically supported by a degree in computer science or related field. Familiarity with tools like TensorFlow, PyTorch, Hugging Face Transformers, and cloud platforms, as well as experience with APIs and version control systems, is common. Excellent problem-solving, communication, and the ability to quickly adapt to new technologies help you stand out in this freelance or project-based role. These skills are critical for efficiently developing, fine-tuning, and deploying sophisticated language models that meet client requirements.

What are some common challenges contract LLM developers face when working with clients on AI projects?

Contract LLM Developers often encounter challenges such as aligning client expectations with the current capabilities and limitations of large language models, ensuring data privacy and compliance, and integrating AI solutions into existing systems. Communication is key, as clients may not fully understand the technical constraints or required data preparation. Additionally, managing project scope and timelines while balancing multiple stakeholders' input can require strong project management and negotiation skills.

What is the difference between Contract Llm Developer vs Contract Software Engineer?

AspectContract Llm DeveloperContract Software Engineer
Required CredentialsTypically requires a law degree, LLM specialization, and legal certificationsRequires a computer science degree or related technical certifications
Work EnvironmentLegal firms, AI companies focusing on legal tech, or law departmentsTech companies, software development firms, or startups
Industry UsageLegal tech, AI legal applications, compliance toolsGeneral software development, AI, and tech industries
Common Search/ComparisonYesYes

The Contract Llm Developer specializes in legal language models, requiring legal expertise and an LLM degree, often working within legal tech or law-related industries. In contrast, a Contract Software Engineer focuses on software development skills and technical certifications, working across various tech sectors. While both roles involve AI and contract work, their core skills and industry applications differ significantly.

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

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

What are popular job titles related to Contract Llm Developer jobs in Nevada?

For Contract Llm Developer jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Contract Llm Developer jobs in Nevada look for?

The top searched job categories for Contract Llm Developer jobs in Nevada are:

What cities in Nevada are hiring for Contract Llm Developer jobs?

Cities in Nevada with the most Contract Llm Developer job openings:

Cloud Solutions Architect / Database Engineer / AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

Reno, NV

$150K - $180K/yr

Full-time

Posted 17 days ago


Job description

We are seeking a highly experienced Cloud Solutions Architect / Database Engineer / AI Platform Architect to design and build the cloud, database, security, API, and AI infrastructure that supports our enterprise applications. Compensation for thisrole will bebetween $150k-$180k depending on experience. This role will be responsible for establishing scalable cloud architecture, designing and engineering production databases, developing secure APIs and integration services, implementing authentication and application security standards, and architecting the AI foundation of our applications.

The architect will build the backend and AI service layers that allow front-end developers to securely and efficiently consume application data, business functionality, and AI-powered capabilities.The ideal candidate will have deep expertise in cloud architecture, C#/.NET, SQL Server, database engineering, REST APIs, application security, authentication, Azure or AWS, enterprise integrations, and production AI architecture . This individual should be capable of taking business and application requirements and translating them into secure, scalable, production-ready technical solutions. Experience with AI and Large Language Model (LLM) platforms is required, particularly when designing the infrastructure, data access, security, APIs, and application architecture necessary to support AI-powered enterprise solutions

The ideal candidate will have hands-on experience building production AI applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or comparable LLM technologies, including designing workflows that enable AI to execute complex business processes through structured instructions, examples, retrieval strategies, orchestration, and enterprise data integration. This role requires experience developing AI as an operational component of an application, not simply integrating an AI API or adding chatbot functionality. Responsibilities Architect and implement scalable, secure, and highly available cloud environments for enterprise applications.

Design the overall backend architecture supporting web applications, internal systems, integrations, and AI-powered solutions. Design, build, and maintain production database environments, including schemas, tables, relationships, stored procedures, views, indexing strategies, and data-access patterns. Develop and optimize SQL Server databases for performance, scalability, reliability, data integrity, and security.

Establish database standards covering data modeling, normalization, indexing, query optimization, auditing, backup, recovery, and disaster recovery. Design and develop secureRESTful APIs and backend services using C#, ASP.NET Core, and related .NET technologies. Build well-structured API and service layers that allow front-end developers to consume data and business functionality without requiring direct access to backend systems or databases

Define API contracts, request/response models, validation standards, error handling, versioning, documentation, and integration patterns. Implement authentication and authorization solutions using technologies and standards such asOAuth 2.0, OpenID Connect, JWT, SSO, RBAC, and enterprise identity providers. Design and enforce application and API security standards, including SSL/TLS, encryption, secrets management, certificate management, secure configuration, and least-privilege access

Implement secure communication between cloud services, databases, APIs, external systems, AI services, and front-end applications. Design cloud networking and infrastructure components including application hosting, databases, storage, identity, networking, firewalls, gateways, load balancing, monitoring, logging, and availability strategies. Develop integration architectures for internal systems, third-party applications, vendor APIs, and enterprise platforms.

Design data pipelines, ETL processes, data transformation services, and system-to-system integrations where required. Establish logging, monitoring, auditing, alerting, and observability standards across backend services and cloud infrastructure. Design scalable architectures capable of supporting increasing users, transaction volumes, data volumes, integrations, AI workloads, and application workloads.

Implement caching, asynchronous processing, queues, background services, and other distributed architecture patterns when appropriate. Develop and maintain CI/CD pipelines and infrastructure deployment processes. Work closely with front-end developers to define API requirements, data contracts, authentication flows, AI service interactions, and integration standards.

Design and implement AI workflow architectures that enable Large Language Models to perform complex business functions by defining process sequences, system instructions, prompt strategies, retrieval mechanisms, examples, evaluation methods, tool interactions, and orchestration workflows. Architect AI systems capable of incorporating enterprise knowledge and business processes through structured process definitions, contextual examples, retrieval, tool use, and iterative refinement so that AI can reliably execute operational business tasks. Design Retrieval-Augmented Generation (RAG) architectures that securely retrieve relevant enterprise information from databases, documents, APIs, vector stores, and other approved business data sources.

Design secure AI integration patterns that control how LLMs access enterprise databases, APIs, internal systems, and sensitive business information. Establish AI evaluation, testing, monitoring, and quality standards to measure accuracy, reliability, consistency, security, and effectiveness of AI-powered workflows. Collaborate with business stakeholders and development teams to translate application requirements and business processes into technical and AI architectures.

Evaluate technical risks, scalability requirements, security concerns, infrastructure costs, AI usage costs, and architectural tradeoffs. Conduct architecture and code reviews and establish backend, database, API, cloud, security, and AI development standards. Provide technical leadership and mentoring to developers working within the architecture.