AI Architect/Gen AI

Infosys Finacle; Bengaluru; On-site; INR 450,000 - 1,100,000; Full time

Job summary

Infosys Finacle seeks an AI/ML Architect to lead design, development and deployment of scalable AI/ML and Generative AI solutions. You will define enterprise AI architecture, drive innovation, and partner with business and tech teams to deliver AI-powered platforms.

Responsibilities include end-to-end AI/ML architectures, data pipelines, model training, MLOps, governance, and cloud-native deployments. Strong leadership and hands-on expertise required.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 10+ years of software engineering experience with at least 5+ years in AI/ML architecture roles.
• Proven experience delivering enterprise AI/ML solutions from concept to production.

Responsibilities

• Design end-to-end AI/ML architectures for enterprise-scale applications.
• Define technology stack, architecture patterns, and deployment strategies for AI solutions.
• Architect scalable data pipelines, model training frameworks, and MLOps processes.
• Ensure AI solutions meet performance, security, scalability, and compliance requirements.

Skills

AI Architecture

Data pipelines

Python/Java/Go/Rust

MLOps

Cloud platforms

Generative AI/LLMs

Vector databases

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

TensorFlow

PyTorch

LangChain

LlamaIndex

Docker

Kubernetes

SageMaker/Azure ML

Job description

We are seeking a highly experienced AI/ML Architect to lead the design, development, and deployment of scalable Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions. The ideal candidate will define enterprise AI architecture, drive innovation, and collaborate with business and technology teams to deliver impactful AI-driven products and platforms.

Key Responsibilities

• Design end-to-end AI/ML architectures for enterprise-scale applications.
• Define technology stack, architecture patterns, and deployment strategies for AI solutions.
• Architect scalable data pipelines, model training frameworks, and MLOps processes.
• Ensure AI solutions meet performance, security, scalability, and compliance requirements.

Generative AI & LLM Solutions

• Design and implement solutions using Large Language Models (LLMs) such as GPT, Llama, Claude, Mistral, or Gemini.
• Build RAG (Retrieval-Augmented Generation) architectures leveraging vector databases and enterprise knowledge repositories.
• Lead development of GenAI use cases such as intelligent assistants, document intelligence, knowledge management, and automation.
• Architect data ingestion, transformation, storage, and feature engineering pipelines.
• Work with cloud-native AI services and modern data platforms.
• Define standards for data governance, model monitoring, and AI lifecycle management.

MLOps & AI Governance

• Establish CI/CD pipelines for ML model deployment and monitoring.
• Define frameworks for model versioning, explainability, observability, and responsible AI practices.
• Implement AI governance frameworks addressing security, privacy, bias, and ethical AI considerations.

Stakeholder & Technical Leadership

• Partner with business stakeholders to identify AI opportunities and translate them into technical solutions.
• Provide technical leadership and mentor data scientists, ML engineers, and development teams.
• Drive AI strategy, roadmap planning, and technology evaluation initiatives.

Required Skills & Qualifications

Experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• 10+ years of software engineering experience with at least 5+ years in AI/ML architecture roles.
• Proven experience delivering enterprise AI/ML solutions from concept to production.

Technical Skills

• Strong expertise in Machine Learning, Deep Learning, NLP, and Generative AI.
• Hands-on experience with Python or Java or Golang or Rust.
• Expertise in AI frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, LlamaIndex.
• Experience with Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS, Milvus).
• Strong understanding of RAG, Prompt Engineering, Agentic AI, and Multi-Agent architectures.
• Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, Azure ML, or Vertex AI.
• Knowledge of cloud platforms: Azure, AWS, or Google Cloud.
• Experience with Docker, Kubernetes, CI/CD, and microservices architecture.