GenAI Engineer (LLM Applications on Azure)

Luxoft Poland; Polska; On-site; PLN 320,000 - 520,000; Full time

Job summary

Luxoft Poland is seeking an expert-level engineer to design and build LLM applications and agentic workflows on Azure, covering RAG pipelines, multi-agent orchestration, MCP tool integration, evaluation, guardrails and cost control. You will set GenAI engineering standards for the account and own solution quality against defined evaluation thresholds.

You will lead the implementation of LLM capabilities across the stack, including LangGraph/LangChain/Semantic Kernel, RAG design, and MCP servers,

Qualifications

• Bachelor's degree or equivalent practical experience.
• 10+ years in software or data engineering, 3+ in ML/NLP and 2+ delivering production LLM applications on Azure OpenAI.
• Expert Python; LangGraph, LangChain and/or Semantic Kernel; asynchronous, event-driven design.
• RAG design with embeddings, vector databases (FAISS, Pinecone), hybrid search and re-ranking.
• MCP server/client development and multi-agent orchestration.
• LLM evaluation and fine-tuning (LoRA/PEFT) and model selection.
• Guardrails and LLM observability (LangSmith, OpenTelemetry).
• Cost optimization and FinOps for inference.

Responsibilities

• Build LLM applications and agent workflows on Azure OpenAI.
• Design RAG pipelines: document ingestion, embedding, vector search, retrieval and re-ranking.
• Integrate MCP servers, function calls and multi-agent systems.
• Develop prompts, run evaluations and tune models.
• Implement guardrails and observability; monitor latency and token accounting.
• Optimize costs via routing, caching and batching.
• Document prompts and evaluation results; mentor engineers.

Skills

Python

LangGraph

LangChain

Semantic Kernel

asynchronous

event-driven design

Azure OpenAI

RAG pipelines

multi-agent orchestration

model evaluation

Education

Bachelor's degree in Computer Science, Engineering, Information Systems or related field

Tools

Azure OpenAI

LangGraph

LangChain

Semantic Kernel

MCP servers

Job description

Expert-level engineer designing and building LLM applications and agentic workflows on Azure: RAG pipelines, multi-agent orchestration, MCP tool integration, evaluation, guardrails and cost control. Sets the GenAI engineering standards for the account and is accountable for solution quality against agreed evaluation thresholds.

Responsibilities

• Build LLM applications and agent workflows with LangGraph / LangChain / Semantic Kernel on Azure OpenAI (AWS Bedrock / GCP Vertex a plus).
• Design RAG pipelines: document ingestion, chunking strategies, embeddings, vector search (Azure AI Search, FAISS, Pinecone), hybrid retrieval and re-ranking.
• Integrate enterprise tools and context via Model Context Protocol (MCP) servers and function / tool calling; design multi-agent systems.
• Engineer, version and test prompts; run offline and online evaluations (accuracy, grounding, hallucination rate) and fine-tuning where justified.
• Implement responsible-AI guardrails (content filters, PII redaction, policy checks) and LLM observability (tracing, token accounting, latency).
• Optimise token and inference cost (model routing, caching, batching); report against cost budgets.
• Document prompts, evaluation results and model choices; mentor engineers adopting GenAI patterns.

Must have

• Bachelor's degree in Computer Science, Engineering, Information Systems or a related field, or equivalent practical experience.
• 10+ years in software or data engineering, of which 3+ in machine learning / NLP and 2+ delivering production LLM applications (RAG, agents) on Azure OpenAI or equivalent.
• Expert Python; LangGraph, LangChain and/or Semantic Kernel; asynchronous, event-driven application design.
• RAG design: chunking, embeddings, vector databases (Azure AI Search, FAISS, Pinecone), hybrid search, re-ranking.
• MCP server / client development, function calling, multi-agent orchestration and state management.
• LLM evaluation (RAGAS, promptfoo, Azure AI evaluation or equivalent), fine-tuning (LoRA / PEFT) and model selection.
• Guardrails (Azure AI Content Safety, NeMo Guardrails or similar), LLM observability (LangSmith, OpenTelemetry), FinOps for inference.

Nice to have

• AWS Bedrock or GCP Vertex AI.
• Azure AI Engineer Associate (AI-102) or equivalent.
• Experience in financial services, sovereign wealth / investment holding or other regulated enterprise environments.
• Experience working with distributed teams (onsite UAE with nearshore India / offshore Poland squads).