Your tasks
- Build Generative AI Solutions:
- Design and implement LLM based solutions aligned to business needs
- Build and refine AI agents capable of reasoning, taking actions, interacting with data sources, and orchestrating workflows
- Apply solid knowledge of ML and LLM concepts to choose models, design prompts, understand training processes conceptually (even if not performing training), and operate models responsibly
- Implement and optimize deployment strategies in production environments
- Improve model performance through structured evaluation, quality measurement, hallucination reduction, and safety guardrails
- Platform, Cloud & Operations:
- Deploy LLM and agent based solutions on cloud infrastructure (preferably Azure)
- Ensure reliability, observability, and efficient resource usage for LLM workloads
- Apply best practices in identity, access control, data protection, and enterprise security policies
- Collaboration & Documentation:
- Work closely with business stakeholders, domain experts, architects, and software engineers to integrate AI into real processes
- Produce high quality documentation: solution designs, architecture diagrams, guidelines, troubleshooting steps, and user facing material
- Translate complex AI concepts into clear, actionable content for technical and non technical audiences
- Training & Support
- Create best practices, enablement materials, and usage guidelines for Generative AI
- Serve as a trusted advisor for internal teams adopting AI Technologies
- Support troubleshooting and ensure consistent, responsible AI adoption across the organization
Who we are looking for
- Bachelor’s degree in Information Technology, Data Management, Business Intelligence, or a related field
- Strong understanding of Machine Learning fundamentals and modern AI concepts
- Hands on experience building AI agents using LLMs (tool interaction, planning, context management, reasoning). Experience with Microsoft Copilot Studio or Microsoft 365 integrations beneficial
- Deep understanding of how LLMs work (prompting, context windows, parameters, evaluation, responsible use, performance measurement) Practical experience with inference and deployment Workflows
- Proficiency in Python and ability to write clean, maintainable, well structured code
- Knowledge of cloud platforms, preferably Azure (compute, security, networking, identity, and AI related services)
- Strong communication skills and ability to work with stakeholders
- Ability to produce excellent documentation
- Innovation driven and proactive in exploring new ideas and approaches
- Familiarity with enterprise document ecosystems or retrieval pipelines and exposure to MLOps, cloud native practices, or monitoring tools are nice to have
