Senior AI Engineer

Role Summary

We are seeking a skilled and AI Engineer to design, develop, and deploy scalable Generative AI and Agentic AI solutions. In this role, you will lead the end-to-end technical delivery of enterprise-grade conversational platforms and intelligent agents capable of autonomous decision-making and tool use. You will act as an architecture owner, driving decisions on Large Language Model (LLM) behavior, Retrieval-Augmented Generation (RAG) implementation, and production readiness.

Key Responsibilities

• Agentic System Architecture: Design and architect multi-agent systems, planners, and collaborative agent frameworks.
• LLM Engineering: Configure and fine-tune foundation models (such as GPT-4o, Claude, or Llama) and develop modular prompt pipelines for dynamic reasoning.
• RAG Implementation: Build and operationalize RAG pipelines for enterprise knowledge access, including document chunking, embedding generation, and similarity search.
• Memory & Context Management: Design short-term and long-term memory architectures, leveraging vector databases (e.g., Pinecone, Milvus, Weaviate) and semantic memory pipelines.
• Evaluation & Observability: Implement sophisticated evaluation frameworks to measure Task Adherence, Tool Call Accuracy, and Intent Resolution using tools like the Azure AI Evaluation library and LangSmith.
• MLOps & LLMOps: Establish CI/CD pipelines for continuous integration, delivery, and monitoring of AI models using Azure DevOps or GitHub Actions.
• Security & Compliance: Ensure data sovereignty and implement safety mechanisms, such as Azure AI Content Safety filters and PII handling, to mitigate hallucinations and ensure responsible AI practices.

Technical Requirements

• Experience: 5–6 years of software engineering experience, with at least 2–3 years specifically dedicated to building and deploying LLM-based solutions in production.
• Cloud Proficiency: Hands-on expertise with Microsoft Azure (Azure OpenAI, Azure AI Foundry, Microsoft Fabric), Google Cloud Platform (Vertex AI), or AWS.
• Programming: High proficiency in Python is mandatory; experience with JavaScript/TypeScript or C# is highly desirable.
• AI Frameworks: Deep expertise in LangChain, LlamaIndex, and major ML frameworks like PyTorch or TensorFlow.
• Modern Infrastructure: Mastery of containerization tools like Docker and orchestration platforms like Kubernetes (AKS/GKE).
• API Development: Strong experience in building and managing REST APIs using FastAPI, Flask, or Azure API Management.

Preferred Qualifications

• Advanced Tooling: Familiarity with Microsoft Agent Framework, DSPy, or prompt-based automation and orchestration patterns.
• Certifications: Azure certifications such as Azure AI Engineer Associate or Azure Data Scientist Associate.
• Soft Skills: Proven ability to mentor junior engineers, collaborate with cross-functional teams, and communicate complex technical concepts to non-technical stakeholders.

Key skills/competency

• Senior AI Engineer
• Generative AI
• Agentic AI
• LLM
• RAG
• Python
• LangChain
• LlamaIndex
• Microsoft Azure
• Kubernetes