Tech S And T Cloud Dev-AI Product Engineer-NGTO-Senior-GDSF02

Technical AI Product Engineer Job Summary What Youll Do Build AI Products, Not Just Models

• Design and develop GenAI-powered applications using LLMs, RAG, and agentic workflows
• Translate business problems into measurable AI-driven outcomes
• Define evaluation metrics and product success criteria

Engineer Intelligent Systems at Scale

• Build and optimize retrieval-augmented generation (RAG) pipelines
• Develop agent-based AI systems with tool usage and orchestration
• Deploy solutions on cloud-native architectures (Azure preferred)

Own the AI Lifecycle (GenAI Ops)

• Implement prompt engineering strategies, embeddings, and fine-tuning approaches
• Build evaluation frameworks and guardrails for reliability and safety
• Enable continuous monitoring of quality, latency, and cost

Drive Responsible & Secure AI

• Embed responsible AI practices (bias detection, explainability, moderation)
• Ensure data privacy, governance, and compliance standards
• Build systems aligned with enterprise security and trust principles

Collaborate & influence

• Partner with product, data, and engineering teams to prioritize AI features
• Influence enterprise AI architecture and best practices
• Enable teams through reusable AI components and APIs

What You Bring Must-Have Skills

• Strong programming in Python and SQL
• Hands-on experience with GenAI patterns: Prompt engineering, Retrieval-Augmented Generation (RAG), Embeddings & semantic search, Agentic workflows
• Experience with AI/ML frameworks: PyTorch / TensorFlow, Hugging Face, LangChain / Semantic Kernel
• Experience deploying AI solutions on cloud platforms (Azure preferred): Azure OpenAI, Azure ML , Azure AI Search

Engineering & Platform Skills

• Strong foundation in data processing (Pandas, NumPy, Spark/Databricks)
• Experience with MLOps / GenAI Ops: MLflow, pipelines, CI/CD, Docker, Azure DevOps
• Experience building APIs and integrating AI into applications
• Understanding of monitoring, observability, and system reliability

Good-to-Have

• Experience building agent-based or autonomous AI systems
• Cost optimization for LLM workloads
• Multi-modal AI (text, image, voice)
• Frontend integration for AI-driven experiences

Qualifications

• Bachelors or Masters in Computer Science, AI/ Data Engineering, or related field
• 2+ years of experience in AI engineering or development

Additional

• Certifications in AI, genAI or Ganetic AI
• Experience with data governance, security, and compliance standards