Senior GenAI Engineer: Azure LLM & Multi-Agent Architect

Luxoft; Polska; On-site; PLN 260,000 - 520,000; Full time

Job summary

DXC Luxoft is seeking an expert GenAI engineer to design and build LLM applications and agent workflows on Azure OpenAI, with a focus on RAG pipelines, multi-agent orchestration, MCP integration, evaluation, guardrails and cost control.

You will set engineering standards for the GenAI account and ensure solution quality against defined evaluation thresholds while mentoring peers and optimizing costs.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems or related field.
• 10+ years in software or data engineering, including 3+ in ML/NLP.
• 2+ years delivering production LLM applications on Azure OpenAI or equivalent.
• Expert Python and experience with LangGraph, LangChain or Semantic Kernel.
• Experience with MCP server/client development and multi-agent orchestration.
• Familiar with LLM evaluation tools and model fine-tuning.

Responsibilities

• Build LLM applications and agent workflows on Azure OpenAI.
• Design RAG pipelines, embeddings, and vector search strategies.
• Integrate enterprise tools via MCP and multi-agent systems.
• Engineer, version and test prompts; run evaluations and tuning.
• Implement guardrails and observability; manage costs and performance.
• Document decisions and mentor engineers in GenAI patterns.

Skills

Python

LangGraph

LangChain

Semantic Kernel

Asynchronous design

LLM evaluation

Cost optimization

Education

Bachelor's degree in Computer Science/Engineering/IS

Tools

Azure OpenAI

Pinecone

FAISS

LangSmith

OpenTelemetry

MCP servers

Job description

DXC Luxoft is seeking an expert GenAI engineer to design and build LLM applications and agent workflows on Azure OpenAI, with a focus on RAG pipelines, multi-agent orchestration, MCP integration, evaluation, guardrails and cost control.

You will set engineering standards for the GenAI account and ensure solution quality against defined evaluation thresholds while mentoring peers and optimizing costs.