Our Customer:
Our customer is driving enterprise innovation through Artificial Intelligence, cloud technologies, and modern engineering practices to solve complex business challenges. The team develops scalable AI-powered solutions that accelerate digital transformation while ensuring enterprise-grade security, governance, and operational excellence.
Your Tasks:
- Analyze ambiguous business challenges and translate them into AI-native solutions with clear business value and measurable outcomes.
- Collaborate with business stakeholders across different functions to understand requirements, identify AI opportunities, and shape practical solutions.
- Design and develop AI solutions from proof-of-concepts and MVPs to scalable, production-ready implementations.
- Design and implement RAG pipelines, AI copilots, intelligent assistants, and agentic AI workflows.
- Develop production-grade AI applications using Microsoft Azure, AI Foundry, Databricks, and Azure OpenAI.
- Develop and configure AI agents and copilots using Copilot Studio, including topics, actions, and integrations with enterprise data sources.
- Design and implement agentic and multi-agent architectures, including planner/executor and supervisor patterns, tool use, and autonomous workflows.
- Establish AI guardrails, evaluation frameworks, validation processes, and responsible AI practices.
- Define and implement approaches for AI-output quality testing, offline and online evaluation, and continuous quality improvement.
- Collaborate with full-stack and frontend engineers to integrate AI capabilities into enterprise applications and user-facing solutions.
- Work closely with QA teams on AI-output quality testing and validation.
- Develop APIs, microservices, and integrations supporting AI capabilities within enterprise environments.
- Deploy, maintain, and optimize AI components and services in Azure environments.
- Monitor AI solution performance, reliability, quality, scalability, and operational costs.
- Prepare architecture diagrams, technical documentation, design documents, READMEs, and implementation guidelines.
- Contribute to reusable AI engineering practices, frameworks, and delivery standards across the organization.
- Take ownership of technical deliverables and work independently with minimal supervision while collaborating effectively within cross-functional teams.
Required Experience and Skills:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field.
- 5+ years of experience in Software Engineering, Data Engineering, or related technical roles.
- 2+ years of hands-on experience building and deploying LLM-powered applications in production environments.
- Strong Python programming skills with experience delivering clean, maintainable, production-grade software.
- Hands-on experience with LLM application and agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar technologies.
- Proven experience developing production-grade agentic AI solutions, including multi-agent systems, tool integration, autonomous workflows, and agent orchestration.
- Hands-on experience with Microsoft Copilot Studio, including building agents/copilots, configuring topics and actions, and integrating with enterprise data sources.
- Strong understanding of Retrieval-Augmented Generation (RAG), including document chunking, embeddings, retrieval strategies, and evaluation techniques.
- Experience with vector databases and semantic search technologies such as Azure AI Search, pgvector, Pinecone, or Weaviate.
- Strong understanding of prompt engineering and structured output design.
- Experience with AI evaluation and observability using tools such as LangSmith, Langfuse, or in-house evaluation frameworks, including offline and online quality measurement.
- Understanding of multi-agent architectures and orchestration patterns such as planner/executor and supervisor approaches.
- Hands-on experience with Microsoft Azure, Azure AI Foundry, Azure OpenAI, and Databricks.
- Experience building APIs, microservices, and cloud-based integrations for AI applications.
- Experience implementing CI/CD pipelines for AI workloads using Git and modern Agile development practices.
- Working knowledge of API/web service security and enterprise data security practices.
- Familiarity with frontend or UI technologies such as React or Streamlit, sufficient to integrate AI capabilities into user-facing applications.
- Strong communication skills with the ability to explain AI capabilities and translate technical solutions into business value.
- Strong organizational and time-management skills and the ability to work effectively in ambiguous environments.
- Excellent written and verbal English.
Would Be a Plus:
- Experience delivering AI solutions in regulated industries such as pharmaceuticals, healthcare, or financial services.
- Experience with Microsoft Power Platform, including Power Automate, Power Apps, Dataverse, or Power Pages.
- Experience with model fine-tuning, distillation, model adaptation, or optimization techniques.
- Experience with enterprise AI governance, validation, safety, compliance, or responsible AI practices.
- Experience contributing to open-source LLM, AI, or agent-based technology projects.
- Experience working with enterprise knowledge-management, AI assistant, or AI-powered search solutions.
Working conditions
5-day working week, 8-hour working day;
Remote work.