Our Customer:
A global enterprise organization building modern data, analytics, and AI solutions within a Microsoft-first ecosystem. The company focuses on scalable and secure enterprise platforms that support business intelligence and digital transformation.
Your Tasks:
Analyze business needs and identify opportunities where AI technologies can create measurable business value
Translate business challenges into practical AI-driven solutions with clear business outcomes
Rapidly prototype, validate, and evolve AI solutions from proof-of-concept to production-ready systems
Build knowledge-driven applications, intelligent assistants, and automated AI workflows
Design and implement retrieval-based solutions, AI-powered services, and agent-oriented architectures
Create scalable backend services and integrations supporting AI capabilities
Establish evaluation, monitoring, governance, and quality-control processes for AI solutions
Prepare technical documentation, architecture diagrams, and implementation guidelines
Collaborate with engineering, product, and quality assurance teams throughout the delivery lifecycle
Deploy, maintain, and optimize AI workloads within Azure environments
Monitor solution quality, performance, scalability, and operational costs
Take ownership of technical deliverables while contributing effectively within cross-functional teams
Required Experience and Skills:
4+ years of experience in Software Engineering, Data Engineering, Machine Learning, or AI-related roles
2+ years of hands-on experience building and deploying LLM-powered applications in production environments
Strong Python development skills with experience delivering production-grade software
Experience working with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar technologies
Practical experience developing intelligent agents, autonomous workflows, or agent-based AI systems
Strong understanding of retrieval-based architectures, embeddings, vector search, and information retrieval concepts
Experience working with vector databases and semantic search technologies such as Azure AI Search, Pinecone, Weaviate, or pgvector
Knowledge of prompt engineering techniques and structured output generation
Experience implementing AI evaluation, observability, monitoring, and quality-assessment processes
Understanding of multi-agent architectures and orchestration patterns
Hands-on experience with Azure-based AI services and application deployment
Experience building APIs, microservices, and distributed applications
Familiarity with CI/CD practices, Git-based workflows, and Agile delivery methodologies
Knowledge of application security, API security, and data protection principles
Ability to integrate AI capabilities into web-based applications and user-facing systems
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field
Excellent written and verbal communication skills in English
Would be a Plus:
Experience with Azure AI Foundry, Azure OpenAI, Databricks, or similar enterprise AI platforms
Experience working within regulated industries and compliance-driven environments
Knowledge of AI governance, validation frameworks, and compliance practices
Experience with model customization, fine-tuning, distillation, or optimization techniques
Contributions to open-source AI, Machine Learning, or LLM-related projects
Familiarity with React, Streamlit, or similar UI technologies
