GenAI Engineer (LLM Applications on Azure)

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 a global IT services and consulting company, part of DXC Technology, delivering cutting-edge digital and software solutions worldwide. We partner with leading financial institutions and global enterprises, helping them transform and scale through modern technology.

Join a global community of engineers and be part of building impactful, modern technology solutions!

Project 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.

Mandatory Skills Description:

• 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.
• 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 Skills Description:

• AWS Bedrock or GCP Vertex AI.
• 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).