Senior Gen AI Engineer (R-19088)

The Role: We are looking for an experienced AI Engineer to design, build, and operationalize AI driven solutions for our global Analytics organization. The ideal candidate will have strong hands on expertise in Python, PySpark, agentic workflow development, and modern GenAI frameworks, with experience building scalable applications using LLMs, retrieval systems, and automation pipelines. You will work closely with data scientists, MLOps engineers, and business stakeholders to build intelligent, production grade systems that power

Key Responsibilities:

1. Agent Development Architecture

   Build agentic workflows using LangChain/LangGraph and similar frameworks.

   Develop autonomous agents for data validation, reporting, document processing, and domain workflows.

   Deploy scalable, resilient agent pipelines with monitoring and evaluation.

2. GenAI Application Engineering

   Develop GenAI applications using models like GPT, Gemini, and LLaMA.

   Implement RAG, vector search, prompt orchestration, and model evaluation.

   Partner with data scientists to productionize POCs.

3. Data Platform Engineering

   Build distributed data pipelines (Python, PySpark).

   Develop APIs, SDKs, and integration layers for AI-powered applications.

   Optimize systems for performance and scalability across cloud/hybrid environments.

4. MLOps / LLMOps

   Contribute to CI/CD workflows for AI models deployment, testing, monitoring.

   Implement governance, guardrails, and reusable GenAI frameworks.

5. Collaboration Stakeholder Engagement

   Work with analytics, product, and engineering teams to define and deliver AI solutions.

   Participate in architecture reviews and iterative development cycles.

   Support knowledge sharing and internal GenAI capability building.

Key Skills Requirements:

• 5-8 years of experience in AI/ML engineering, data science, or software engineering, with at least 4 years focused on GenAI.
• Strong programming expertise in Python, distributed computing using PySpark, and API development.
• Hands on experience with LLM frameworks (LangChain, LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs).
• Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestration.
• Solid understanding of GenAI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineering.
• Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AI.
• Strong problem solving, system design thinking, and ability to translate business needs into scalable AI solutions.
• Excellent verbal, written communication and presentation skills.

Good to Have

• Experience in workflow automation and building reusable AI components.
• Background in analytics, statistical models, or enterprise data products.
• Experience with MLOps / LLMOps tooling

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.