Artificial Intelligence Architect

Opus Technologies; Pune District; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Opus Technologies is seeking a hands-on AI Architect with a strong Java background to design and lead GenAI solutions at scale. You will drive architecture for enterprise AI applications using LLMs, RAG, and AI Agents, with governance and secure, scalable deployment in cloud environments.

The role requires 8–12 years in software engineering with Java/Spring Boot, plus 2+ years in AI solution delivery. Strong leadership and collaboration with product and engineering teams are essential.

Qualifications

• 8-12 years of software engineering experience with Java, Spring Boot and microservices.
• 2+ years hands-on experience architecting AI/GenAI solutions.
• Experience designing and implementing RAG-based applications integrating LLMs into enterprise systems.
• Hands-on with Azure OpenAI/OpenAI, LangChain4j, vector databases, and AI orchestration frameworks.
• Strong knowledge of cloud-native architecture, APIs, and enterprise integration patterns.
• Experience with Docker, Kubernetes, and cloud deployment models.

Responsibilities

• Architect and deliver scalable, secure, enterprise-grade AI/GenAI solutions.
• Design and implement applications leveraging LLMs, RAG frameworks, and AI Agents.
• Define AI reference architectures, reusable patterns, and integration strategies.
• Lead technical decision-making across AI platforms, APIs, and enterprise integrations.
• Collaborate with business, product, and engineering teams to translate requirements into solutions.
• Drive AI governance, security, observability, scalability, and operational excellence.
• Lead PoCs, pilot programs, architecture reviews, and production implementations.
• Evaluate emerging AI technologies and recommend adoption strategies.

Skills

Hands-on AI Architect

Java engineering

Leadership

Stakeholder mgmt

Tools

Java

Spring Boot

Microservices

Azure OpenAI/OpenAI

LangChain4j

Vector Databases

AI orchestration frameworks

Docker

Kubernetes

Cloud deployment models

APIs

Enterprise integration patterns

Job description

Job Scope:

We are looking for a hands-on AI Architect with a strong Java engineering background and proven experience building Generative AI solutions at scale. In this role, you will architect, design, and lead the delivery of enterprise AI applications leveraging LLMs, RAG, AI Agents, and cloud-native technologies, driving solutions from strategy through production deployment.

Key Responsibilities

• Architect and deliver scalable, secure, and enterprise-grade AI/GenAI solutions.
• Design and implement applications leveraging LLMs, RAG frameworks, and AI Agents.
• Define AI reference architectures, reusable patterns, and integration strategies.
• Lead technical decision-making across AI platforms, APIs, and enterprise integrations.
• Collaborate with business, product, and engineering teams to translate requirements into solutions.
• Drive AI governance, security, observability, scalability, and operational excellence.
• Lead PoCs, pilot programs, architecture reviews, and production implementations.
• Evaluate emerging AI technologies and recommend adoption strategies.

Required Skills & Experience

• 8-12 years of software engineering experience with strong expertise in Java, Spring Boot, and Microservices.
• 2+ years of hands-on experience architecting and delivering AI/Generative AI solutions.
• Experience designing and implementing RAG-based applications and integrating LLMs into enterprise systems.
• Hands-on experience with Azure OpenAI/OpenAI, LangChain4j, Vector Databases, and AI orchestration frameworks.
• Strong knowledge of cloud-native architecture, APIs, and enterprise integration patterns.
• Experience with Docker, Kubernetes, and cloud deployment models.
• Strong technical leadership, stakeholder management, and architecture governance skills.

Preferred Qualifications

• Experience building AI Agent-based solutions and multi-agent workflows.
• Knowledge of Responsible AI, AI security, and governance frameworks.
• Cloud certifications (Azure, AWS, or GCP) are a plus.

Join us to architect next-generation AI platforms and transform enterprise business processes through cutting-edge Generative AI solutions.