Hire LLM Engineers | TeamStation AI

LLM Engineers are the architects of modern AI applications. They bridge the gap between powerful Large Language Models and real-world business problems, designing and building systems that can reason, generate, and interact. We provide elite engineers vetted for their expertise in model integration, prompt engineering, and building robust RAG pipelines.

Are your AI prototypes failing to reach production?

The Problem

Moving from a proof-of-concept in a notebook to a scalable, reliable production service is a massive engineering challenge. Prototypes often lack the necessary error handling, scalability, and observability required for real-world use.

The TeamStation AI Solution

Our LLM Engineers are production-focused. We vet their ability to build robust, scalable services around LLMs, using modern MLOps principles. They build systems with proper logging, monitoring, and automated evaluation to ensure reliability and performance at scale.

Proof: Production-ready, scalable LLM-based services.
Is prompt engineering more art than science for your team?

The Problem

Teams often rely on trial and error to create prompts, leading to inconsistent model behavior and unreliable outputs. This makes it impossible to build a predictable application.

The TeamStation AI Solution

Our engineers apply a systematic approach to prompt engineering. They are experts in techniques like chain-of-thought, few-shot prompting, and structured output formats (e.g., JSON) to create robust and reliable prompts that guide the model effectively.

Proof: Systematic, reliable, and optimized prompt design.

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 LLM Engineer 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 LLM Engineer 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 LLM Engineer discipline.

Evaluation Focus

Axiom Cortex™ measures their system design skills and architectural instinct specific to the LLM Engineer 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 LLM Engineer across teams, solving your most complex business problems.

Evaluation Focus

We validate their ability to make critical trade-offs related to the LLM Engineer 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 LLM Engineer

LLM API Integration (OpenAI, Anthropic, Google)
Prompt Engineering & Optimization
Retrieval-Augmented Generation (RAG) Architecture
Vector Database Integration
LLMOps and Production Monitoring

Our Technical Analysis for LLM Engineer

Candidates are evaluated on their ability to build an end-to-end RAG system. This includes data ingestion, chunking, embedding, and retrieval from a vector database to augment an LLM prompt. We assess their prompt engineering skills and their ability to design a system that is both accurate and resistant to hallucinations.

Related Specializations

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About TeamStation AI

Learn about our mission to redefine nearshore software development.

Nearshore vs. Offshore

Read our CTO's guide to making the right global talent decision.

Ready to Hire a LLM Engineer Expert?

Stop searching, start building. We provide top-tier, vetted nearshore LLM Engineer talent ready to integrate and deliver from day one.

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