Infosys
Senior GenAI Engineer
Bangalore, India
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- Seniority
- Senior
- Country
- IN
- Work mode
- On-site / unstated
- First seen by hirly
- 27 Sept 2026
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the posting
We are seeking an experienced Senior GenAI Engineer with LangGraph / LangChain, 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 LangChain, LangGraph, 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.
Responsibilities
Generative AI Development
Design and implement enterprise GenAI applications using LLMs.
Develop multi-agent workflows and agentic AI systems using LangGraph.
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.
Technical requirements
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 PySpark.
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.
Additional responsibilities
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
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