
Senior GenAI Engineer
About the role
We are seeking an experienced Senior GenAI Engineer with Lang Graph / Lang Chain, MLflow to design, build, and deploy enterprise-scale Generative AI solutions leveraging LLMs, RAG architectures, and modern data platforms. The ideal candidate should possess strong expertise in Lang Chain, Lang Graph, MLflow, Databricks, PySpark, and production-grade AI deployment frameworks.
The role involves building scalable AI applications, developing intelligent agents, optimizing retrieval systems, and collaborating with data engineering and product teams to deliver impactful AI solutions.
Generative AI Development:
Design and implement enterprise GenAI applications using LLMs.
Develop multi-agent workflows and agentic AI systems using Lang Graph.
Build conversational AI, copilots, knowledge assistants, and intelligent automation solutions.
Engineer prompts and workflows to optimize model performance and user experience.
RAG & Knowledge Systems:
Design and implement Retrieval-Augmented Generation (RAG) pipelines.
Integrate vector databases and document retrieval frameworks.
Optimize document chunking, embeddings, indexing, retrieval, and reranking strategies.
Improve response accuracy, latency, and relevance of AI systems.
AI Platform Engineering:
Build scalable AI platforms on Databricks and cloud environments.
Develop model lifecycle management solutions using MLflow.
Implement model tracking, versioning, deployment, monitoring, and governance.
Support MLOps and LLMOps initiatives.
Data Engineering
Build and optimize large-scale data pipelines using Py Spark.
Process structured and unstructured data for AI and analytics workloads.
Collaborate with data engineering teams to build feature and knowledge pipelines.
Ensure data quality, lineage, and governance standards.
Deployment & Productionization:
Deploy and serve models using MLflow and Databricks.
Monitor model performance, drift, and operational metrics.
Implement CI/CD pipelines for AI and machine learning workloads.
Ensure scalability, reliability, and observability of AI services.
Leadership & Mentorship:
Mentor junior engineers and AI practitioners.
Conduct design reviews and architecture discussions.
Define GenAI development standards and best practices.
Collaborate with business stakeholders to identify AI use cases and translate them into solutions.
Education: MCA,MSc,Bachelor of Engineering,BBA,BCom,BCS
Preferred skills: Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)
Benefits and perks
•Learning Budget
About Infosys
BANGALORE
Headquarters