Technical AI Product Engineer

47 Years | Full-time

Job Summary

If you want to move beyond experiments and build AI systems that truly power products and decisionsthis role is for you.

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
- Robust 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

📌 Tech S And T Cloud Dev-AI Product Engineer-NGTO-Senior-G (Noida)
🏢 EY
📍 Noida