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:
Design AI-driven solutions that address complex business challenges and deliver measurable business value.
Collaborate with business stakeholders to understand requirements and translate them into scalable AI applications.
Develop AI solutions from proof-of-concepts and MVPs to production-ready implementations.
Design, build, and optimize Retrieval-Augmented Generation (RAG) pipelines, AI copilots, and agent-based applications.
Develop and deploy AI services using Microsoft Azure technologies, Databricks, and cloud-native architectures.
Establish AI governance practices, including model evaluation, validation, quality assurance, and responsible AI principles.
Collaborate with software engineers, QA teams, and product stakeholders to integrate AI capabilities into enterprise applications.
Monitor AI solution performance, quality, reliability, and operational costs while continuously improving production systems.
Create technical documentation, architecture designs, and implementation guidelines to support long-term maintainability.
Contribute to reusable AI engineering practices, frameworks, and continuous innovation initiatives.
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 experience developing and deploying production-grade Large Language Model (LLM) applications.
Strong Python programming skills with experience building clean, maintainable, production-quality software.
Hands-on experience with AI application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar agent frameworks.
Proven experience developing production-ready agentic AI solutions, including multi-agent systems, autonomous workflows, and tool integration.
Strong understanding of Retrieval-Augmented Generation (RAG), including document chunking, embeddings, retrieval strategies, and evaluation techniques.
Experience working with vector databases such as Azure AI Search, Pinecone, Weaviate, pgvector, or similar technologies.
Experience with prompt engineering and structured output design.
Experience evaluating and monitoring AI applications using observability and evaluation tools such as LangSmith, Langfuse, or similar frameworks.
Experience designing and orchestrating multi-agent architectures using planning, execution, and supervision patterns.
Hands-on experience with Microsoft Azure services, including Azure OpenAI, Azure AI Foundry, Databricks, and cloud-based AI solutions.
Experience developing APIs, microservices, and integrating AI capabilities into enterprise applications.
Experience implementing CI/CD pipelines for AI workloads using Git and modern Agile development practices.
Good understanding of API security, application security, and enterprise data protection principles.
Familiarity with frontend technologies such as React or Streamlit for AI application integration.
Strong communication skills with the ability to translate AI capabilities into business value.
Ability to work independently while collaborating effectively within cross-functional teams.
Fluent English.
Would Be a Plus:
Experience delivering AI solutions within regulated industries such as pharmaceuticals, healthcare, or financial services.
Experience with model fine-tuning, distillation, or other model adaptation techniques.
Contributions to open-source AI, LLM, or agent-based technology projects.
Working conditions
5-day working week, 8-hour working day
Remote wo
