Hire LLM & Generative AI Experts | Nearshore Software Development

Large Language Models (LLMs) are a transformative new technology that is enabling a new generation of intelligent applications. You need an expert who can navigate the rapidly evolving landscape of LLMs and apply them to solve real business problems. Our vetting process, powered by Axiom Cortex™, finds engineers who are at the forefront of this new field. We test their ability to work with models from OpenAI, Anthropic, and open-source providers, and to build complex applications using frameworks like LangChain and LlamaIndex.

Are your LLM-powered features unreliable and prone to 'hallucinations'?

The Problem

LLMs are powerful, but they can also be unpredictable and make things up. Building a reliable application on top of them requires a deep understanding of their limitations and how to mitigate them.

The TeamStation AI Solution

We vet for engineers who are experts in building reliable LLM applications. They must demonstrate the ability to use techniques like Retrieval-Augmented Generation (RAG) to ground the model in your own data, reducing hallucinations and improving accuracy.

Proof: Reliable and Factual LLM-Powered Applications
Are you struggling to move your LLM prototypes into production?

The Problem

Building a production-ready LLM application involves more than just calling an API. You need to manage prompts, handle context, evaluate performance, and deploy your application in a scalable and cost-effective way.

The TeamStation AI Solution

Our engineers are proficient in the emerging field of LLMOps. They are vetted on their ability to use tools and best practices to build, deploy, and monitor LLM applications at scale, ensuring they are reliable, performant, and cost-effective.

Proof: Production-Ready LLM Applications

How We Measure Seniority: From L1 to L4 Certified Expert

We don't just match keywords; we measure cognitive ability. Our Axiom Cortex™ engine evaluates every candidate against a 44-point psychometric and technical framework to precisely map their seniority and predict their success on your team. This data-driven approach allows for transparent, value-based pricing.

L1 Proficient

Guided Contributor

Contributes on component-level tasks within the LLMs (Large Language Models) domain. Foundational knowledge and learning agility are validated.

Evaluation Focus

Axiom Cortex™ validates core competencies via correctness, method clarity, and fluency scoring. We ensure they can reliably execute assigned tasks.

$20 /hour

$3,460/mo · $41,520/yr

± $5 USD

L2 Mid-Level

Independent Feature Owner

Independently ships features and services in the LLMs (Large Language Models) space, handling ambiguity with minimal supervision.

Evaluation Focus

We assess their mental model accuracy and problem-solving via composite scores and role-level normalization. They can own features end-to-end.

$30 / hour

$5,190/mo · $62,280/yr

± $5 USD

L3 Senior

Leads Complex Projects

Leads cross-component projects, raises standards, and provides mentorship within the LLMs (Large Language Models) discipline.

Evaluation Focus

Axiom Cortex™ measures their system design skills and architectural instinct specific to the LLMs (Large Language Models) domain via trait synthesis and semantic alignment scoring. They are force-multipliers.

$40 / hour

$6,920/mo · $83,040/yr

± $5 USD

L4 Expert

Org-Level Architect

Sets architecture and technical strategy for LLMs (Large Language Models) across teams, solving your most complex business problems.

Evaluation Focus

We validate their ability to make critical trade-offs related to the LLMs (Large Language Models) domain via utility-optimized decision gates and multi-objective analysis. They drive innovation at an organizational level.

$50 / hour

$8,650/mo · $103,800/yr

± $10 USD

Pricing estimates are calculated using the U.S. standard of 173 workable hours per month, which represents the realistic full-time workload after adjusting for federal holidays, paid time off (PTO), and sick leave.

Core Competencies We Validate for LLMs (Large Language Models)

LLM fundamentals and model selection (OpenAI, Anthropic, open-source)
Prompt engineering and optimization
Retrieval-Augmented Generation (RAG) with vector databases
Fine-tuning and model customization
LLMOps (deployment, monitoring, evaluation)

Our Technical Analysis for LLMs (Large Language Models)

The LLM evaluation focuses on the practical application of large language models. Candidates are required to build a complete LLM-powered application, such as a question-answering system over a set of documents. A critical assessment is their ability to implement a robust RAG pipeline, including document chunking, embedding, and retrieval. We also test their prompt engineering skills and their ability to fine-tune a model for a specific task. Finally, we assess their understanding of the operational challenges of running LLM applications in production.

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