Senior Generative AI Engineer Contract

Job Description
Role: Senior / Lead Generative AI Engineer
Total Experience: 7+ Years AI/ML | GenAI Experience: 3+ Years
Key Responsibilities
Lead the design, architecture, and delivery of end-to-end Generative AI solutions, taking technical ownership from concept to production.
Architect, build, and scale production-grade RAG-based chatbot solutions using enterprise data and Azure-native GenAI services.
Define and implement robust RAG architectures leveraging Azure AI Foundry, Azure Cognitive Search, vector databases, and embedding pipelines.
Drive best practices for LLM optimization, including prompt engineering strategies, retrieval tuning, context optimization, latency reduction, and cost optimization.
Develop reliable backend and orchestration layers using Python and Azure Functions, ensuring scalability and fault tolerance.
Lead CI/CD and DevOps pipelines for GenAI applications, supporting rapid iteration and safe production releases.
Establish monitoring, evaluation, and observability standards for GenAI systems, ensuring quality, reliability, and Responsible AI compliance.
Offer technical guidance and support to working team, while remaining hands-on with critical components of solution development.
Partner with product, data, and business teams to translate enterprise use cases into scalable GenAI architectures with measurable impact.
Technical Skills & Experience
7+ years of overall engineering experience, with 3+ years of hands-on Generative AI delivery.
Demonstrated experience building and maintaining production-grade RAG-based chatbot applications.
Experience in designing API endpoints & Integration.
Deep understanding of LLMs, Generative AI patterns, and enterprise conversational AI design.
Strong hands-on experience with Azure AI Foundry, Azure OpenAI / LLM services, and Azure-native AI deployments. Or, cloud services equivalent to such.
Solid expertise in Azure Cognitive Search, vector databases, and semantic retrieval techniques. Or, cloud services equivalent to such.
Strong Python programming skills for GenAI workflows, APIs, and backend systems.
Experience with Azure Functions and cloud-native application development.
Proven experience delivering production deployments with DevOps pipelines, monitoring, and operational excellence.
Good to Have
Background in data science and machine learning, including classical ML concepts and workflows.
Familiarity with MLOps practices, experimentation frameworks, and model monitoring.
Experience optimizing large-scale AI systems for performance, reliability, and cost efficiency.
Education & Qualifications
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
Relevant certifications in Azure AI, Generative AI, or cloud platforms are a plus.