Hire engineers who've already solved challenges your projects are facing today. BUSoft's staff augmentation provides specialists who help you ship more efficiently and hand the know-how to your team. Start with one engineer and add more when you need them.
Pre-vetted by practitioners
You run the interviews
Replacement guarantee
Specializations
Each practice is staffed by engineers who work on that platform full-time.
Choose the one your project needs.
AI Developers
Your RAG pipelines and agents move from prototype to production, with evaluation built in.
Data Engineers
Pipelines arrive with lineage and tests, so downstream numbers hold up.
ServiceNow Developers
Scoped apps keep your ITSM, ITOM and CSM work clean through every upgrade.
Snowflake Developers
Warehouse sizing and query tuning keep your credit spend predictable.
Databricks Engineers
We deploy Delta Lake and Spark as code, governed by Unity Catalog.
Why specialized talent
A missing skill usually leaves two options: train a generalist on your timeline, or commission a full team for one role. Specialist staff augmentation adds a third. You bring in the engineer who has already solved this problem, and everything else stays as it is.
AI
Data
ServiceNow
Snowflake
Databricks
Specialists, not generalists
Each engineer works in one of five practices, every day, so your Snowflake hire has delivered Snowflake projects in production
Productive in the first sprint
Specialists know the problem, so discovery is a quick run-through. Pre-screened, they usually contribute from sprint one.
Fewer expensive mistakes
Most expensive platform mistakes happen the first time. Experienced engineers have seen them before and know how to avoid them.
A practice behind
every hire
Every hire is backed by their whole practice, so you get higher standards, faster backfill and more specialists when needed.
Technology expertise
Select a practice to see what its engineers bring. If your stack isn't listed, ask,
and a practice lead will tell you plainly whether we fit.
How we engage
Models & Providers
Frontier and open-weight models, selected for the job rather than the hype.
Claude
GPT
Gemini
Llama
Mistral
Amazon Bedrock
Agents & Orchestration
Tool use, multi-step workflows and the plumbing that keeps them predictable.
LangChain
LangGraph
LlamaIndex
MCP
CrewAI
Retrieval & Vector Stores
Embedding pipelines, chunking strategy and search that actually returns the right context.
pgvector
Pinecone
Weaviate
Qdrant
FAISS
Milvus
Training & Fine-tuning
Adapting models to your domain when prompting and retrieval are not enough.
PyTorch
Hugging Face
PEFT / LoRA
DeepSpeed
Ray Train
Serving & Inference
Throughput, latency and cost per token treated as first-class design constraints.
vLLM
TensorRT-LLM
ONNX Runtime
Triton
KServe
Evaluation & Observability
Benchmarks, regression suites and tracing, so model changes are measured not guessed.
LangSmith
Ragas
DeepEval
promptfoo
Weights & Biases
MLflow
HOw it works
Engagement models
Three Ways to Bring Specialists In
Our approaches are tuned to fit what your project needs. Start with a handful of
specialists and change the shape of how you engage with us as the project changes.
Dedicated Engineer
One specialist, fully allocated to your roadmap, reporting into your team like any other engineer.
Best for
A single deep skill gap
Full-time allocation to your project
Direct reporting into your engineering lead
Works in your tools, rituals and codebase
Scale up or down with notice
Team Extension
A group of specialists who slot into your existing team and share its backlog and standard.
Best for
Fast, low-friction capacity
Multiple engineers across the five
specializations
Embedded in your sprint and review process
Your architecture and standards, our
engineers
Flexible composition as priorities shift
Dedicated Team
A self-contained pod — engineers plus technical lead — owning a defined workstream end to end.
Best for
Owning a whole workstream
Cross-specialization pod built around the outcome
Dedicated technical lead and delivery cadence
Owns delivery, quality and documentation
Clear milestones and reporting
Trust & proof
Work With Engineers Vetted by Practice Experts
250+
Specialists across the
five practices
10 days
Average time to
first interview
95%
Engagement
extension rate
5
Technology
specializations
Vetted Inside the
Specialization
Practitioner-led screening — AI engineers assess AI engineers, while Snowflake architects assess Snowflake developers.
Certified Where
Certification Matters
ServiceNow, Snowflake and Databricks credentials are verified at source and kept current.
Replacement Guarantee
If an engineer is not the right fit, we replace them. Terms are agreed in writing before the engagement begins.
Certifications
Data & Analytics
Build for what’s next
Certified partner
Applied AI
Safer, more capable AI
Certification in progress
Cloud Infrastructure
Scale with confidence
Certified partner
