GenAI Engineer (LLM Applications on Azure)

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.

What we offer

• Global Relocation - (Relocation options; Experience in an international environment; Cross-cultural experience)

• Recognition and Evaluation - (Feedback culture; Regular appraisals)

• Time Off - (Annual holiday - 20 or 26 days. The duration of the leave depends on the overall seniority; Occasional leave - 1 or 2 days/ depending on the circumstances; Child care leave - 2 days or 16 hours per year; Absence due to force majeure - 2 days or 16 hours per year; Maternity Leave - 20 weeks; Parental Leave - 41 weeks; Paternity Leave - 14 days)

• Luxoft Training Center - (Expert-led tech courses covering basic to advanced topics; Internal instructor-led soft skills courses; Comprehensive in-house self-learning resources for both soft and hard skills; Access to external self-learning libraries like ProQuest eBook and Udemy for Business; Cloud Programs: MS Cloud Academy, AWS Partner Academy, Google Cloud Academy; Custom Learning Programs: upskilling, reskilling, technical mentorship; Leadership Programs for Managers)

• Well-being and Work-life Balance - (Multisport card; Possibility to order Multisport card at the corporate rate for family members; LuxGood Program: wellbeing seminars, contests, relaxation sessions, yoga sessions, etc.; One Team Program: Buddy for each New Joiner; seminars, meeting and workplace space to support integration with local community and culture; “Hire me” workshops for partners; Preferential banking offer; Preferential car leasing offer; Cafeteria program discounts for shops, cinema tickets, holiday offers; Luxoft Social Benefit Fund: sport and recreation benefits, the possibility to receive financial support)

• Health Care - (Private Healthcare Insurance with unlimited access to specialists; Full dental support; Travel Insurance; Possibility to add private healthcare coverage for family members at the corporate rate; Life insurance at the corporate rate for employees and family members, including payment of the basic package for the employee by the employer; Reimbursement for corrective glasses)

• Company Events and Friendly Environment - (Many fun social activities organized by the Luxoft team offline in your city; Online entertainment events for whole company and local team events; A workplace where you’re treated with respect within a multicultural team)

• Internal Mobility - (Rotation between projects and accounts; New career opportunities)

• Self-Learning Library

• CSR Projects

Other

• Languages: English: C1 Advanced

• Seniority: Senior

Requirements

• 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.

• Azure OpenAI, Azure AI Search, Azure AI Foundry / ML, Functions, Container Apps / AKS, Key Vault, Application Insights.

• 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.

• AWS Bedrock or GCP Vertex AI.

• Semantic caching, model distillation, small-language-model deployment.

• 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).

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.