What platforms do your development talent specialise in?

Our specialists are vetted for experience across major platforms including Python, Java, Node.js and more - ensuring they deliver value from day one.

How long does onboarding take?

Onboarding is fast and seamless. Once we define your needs, we match you with top-tier web development talent and can have your first hire fully operational in as little as 10 days.

Can I scale to a full team?

Absolutely. Start with one specialist or scale to a full-stack digital team - our flexible model adapts to your needs as you grow. We build around your goals and budget.

LLM engineers | Sourcewiser

LLM engineers specialise in the full lifecycle of large language model development and deployment. They select appropriate base models, design fine-tuning strategies, build retrieval-augmented generation (RAG) pipelines and deploy scalable inference infrastructure - turning raw AI capability into production-ready solutions.

They work at the intersection of machine learning engineering, software development and AI application design. Their expertise is critical for organisations building AI-powered products, internal tools or intelligent automation systems that rely on language understanding at scale.

Sourcewiser's offshore LLM engineers integrate directly into your product or AI team. They bring deep technical proficiency in model selection, fine-tuning, evaluation and inference optimisation - alongside the software engineering discipline required to ship and maintain production AI systems.

Our LLM engineers are experienced with frameworks and tools such as Hugging Face Transformers, PyTorch, LangChain, LlamaIndex, vLLM, OpenAI and Anthropic APIs, AWS SageMaker, Azure ML and vector databases including Pinecone, Weaviate and Chroma.

"Sourcewiser changed how we think about building offshore teams. Instead of a one-size-fits-all model, they took the time to understand what we needed and built a team around that. The result is a group of people in Manila who feel like an extension of our own business."

Daniel, Founder, Hustlr

"Working with the Sourcewiser team in Manila has been fantastic for us at Retail Media Hub. Having a dedicated sales manager and marketing support right in the team makes all the difference, they really get our brand and feel like part of our own crew. The team is proactive, easy to work with, and always focused on helping us grow. It’s been a seamless way to scale up while keeping the quality and energy we want for our customers."

Rob, National Sales Director, Retail Media Hub

Daniel, Founder, Hustlr

Rob, National Sales Director, Retail Media Hub

How it works

STEP 1 Define your needs

We align with your IT and tech goals, roles and unique organisational challenges.

STEP 2 Get matched

We shortlist the top 1% of IT and tech candidates and match to your requirements, tools and culture.

STEP 3 Choose your delivery model

Remote, hybrid or office-based - we build around your preferred setup.

STEP 4 Scale with confidence

You stay in control with ongoing support, performance tracking and delivery optimisation.

Get started now

Design and implement RAG pipelines, fine-tuning workflows and LLM-powered application architectures
Select, evaluate and benchmark foundation models against task-specific performance criteria
Fine-tune open-source and proprietary LLMs using techniques such as LoRA, QLoRA and instruction tuning
Build and maintain inference infrastructure for scalable, low-latency LLM deployment
Evaluate model outputs for accuracy, safety and alignment, iterating on training and prompting strategies

Junior

(1 - 3 years experience)

Implement basic RAG pipelines

Work with pre-trained LLMs via API

Write evaluation scripts and benchmarks
Intermediate

(3 - 5 years experience)

Fine-tune models with LoRA / QLoRA

Build end-to-end LLM applications

Optimise inference for cost and latency
Senior

(5+ years experience)

Architect production LLM systems at scale

Lead model selection and fine-tuning strategy

Design safety, alignment and evaluation frameworks

Paulo

LLM Engineer

Experience: 4+ years

Location: Philippines

Expert in:

RAG pipeline development
Vector database integration

Highlights:

Built RAG system reducing hallucination rate by 52%
Deployed LLM inference API handling 10,000+ requests/day

Clarissa

Senior LLM Engineer

Experience: 7+ years

Location: Philippines

Expert in:

LLM fine-tuning (LoRA, QLoRA)
Multi-agent LLM architectures

Highlights:

Led LLM productionisation for Series B AI startup
Reduced inference cost by 60% via quantisation and batching

Paulo

LLM Engineer

Experience: 4+ years

Location: Philippines

Expert in:

RAG pipeline development
Vector database integration

Highlights:

Built RAG system reducing hallucination rate by 52%
Deployed LLM inference API handling 10,000+ requests/day

Clarissa

Senior LLM Engineer

Experience: 7+ years

Location: Philippines

Expert in:

LLM fine-tuning (LoRA, QLoRA)
Multi-agent LLM architectures

Highlights:

Led LLM productionisation for Series B AI startup
Reduced inference cost by 60% via quantisation and batching

What LLM frameworks and infrastructure do your engineers work with?

Our LLM engineers are proficient across the leading frameworks including Hugging Face Transformers, LangChain, LlamaIndex and PyTorch. For infrastructure, they work with AWS SageMaker, Azure ML and vLLM for high-performance inference, alongside vector stores such as Pinecone, Weaviate and Chroma for RAG systems.

Can your LLM engineers fine-tune models on proprietary data?

Yes. Our engineers are experienced in supervised fine-tuning, instruction tuning and parameter-efficient methods such as LoRA and QLoRA. We ensure appropriate data handling practices and can work within your security and compliance requirements.

How do your LLM engineers handle model evaluation and safety?

Our engineers apply systematic evaluation frameworks covering accuracy, hallucination rate, latency and safety alignment. They build automated evaluation pipelines and work iteratively to improve model performance against defined benchmarks.

Can I hire an LLM engineer to work alongside my existing AI or engineering team?

Absolutely. Our LLM engineers are experienced in embedded team models and work directly within your development workflow, tools and deployment practices — integrating as a natural extension of your team rather than an external resource.

Partner with Sourcewiser for unmatched solutions that deliver results. Whether you're building a new team or augmenting your current capabilities, we're here to help.

Curated hires, no seat-fillers

AI-matched, human-approved

Flexible models, always-on support

Fast deployment, long-term retention

LLM engineers building the language intelligence that powers your products

Don't just take our word for it...

How it works

Key responsibilities

Platform-ready talent,
vetted for the tools you use

Levels of experience

Junior

Intermediate

Senior

Meet your future team members

Frequently asked questions

What LLM frameworks and infrastructure do your engineers work with?

Can your LLM engineers fine-tune models on proprietary data?

How do your LLM engineers handle model evaluation and safety?

Can I hire an LLM engineer to work alongside my existing AI or engineering team?

Other IT and tech roles you can outsource

Start scaling your IT and tech operations smarter

Need more than IT and tech support?

LLM engineers building the language intelligence that powers your products

Don't just take our word for it...

How it works

Key responsibilities

Platform-ready talent, vetted for the tools you use

Levels of experience

Junior

Intermediate

Senior

Meet your future team members

Frequently asked questions

What LLM frameworks and infrastructure do your engineers work with?

Can your LLM engineers fine-tune models on proprietary data?

How do your LLM engineers handle model evaluation and safety?

Can I hire an LLM engineer to work alongside my existing AI or engineering team?

Other IT and tech roles you can outsource

Start scaling your IT and tech operations smarter

Need more than IT and tech support?

Platform-ready talent,
vetted for the tools you use