Role Summary :

We are looking for a seasoned GenAI Technical Architect with expertise in architecting and implementing enterprise-scale generative AI and agentic AI solutions using Python, Azure AI services, and modern AI frameworks. The role focuses on defining scalable and secure AI architectures across LLMs, prompt engineering, fine-tuning, GenAI SDKs, and multi-agent orchestration, while driving cloud-native solution design using distributed systems, microservices, Docker, Kubernetes, and Azure platforms such as AML, Cognitive Services, Databricks, and AKS.

Primary (Must have skills) :

- Generative AI Expertise : 2-3 years of experience in designing and implementing generative AI solutions, including knowledge of various generative and autoregressive models. Ability to apply generative AI techniques to diverse use cases such as image generation, text generation, and creative content synthesis.

- 2 years of experience in prompt engineering, fine tuning, agentic framework, GenAI SDKs.

- 1-2 years of experience in Agentic AI frameworks like Autogen, Lanngraph, MS Agent SDK, A2A, MCP, A2P, memory concepts, multi agent orchestration.

- 5+ years of experience in Python.

- Azure Proficiency : 3-5 years of experience with Azure cloud services relevant to AI, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Kubernetes Service (AKS). 2+ years of experience in Azure's capabilities to architect end-to-end AI solutions and optimize performance.

- Architecture Design : 3-5 years of skills with the ability to design scalable, reliable, and cost-effective architectures for AI solutions. Proficiency in designing distributed systems, microservices architectures, and containerized solutions using technologies such as Docker and Kubernetes.

Why This Role Matters :

We are looking for a seasoned GenAI Technical Architect with expertise in architecting and implementing enterprise-scale generative AI and agentic AI solutions using Python, Azure AI services, and modern AI frameworks. The role focuses on defining scalable and secure AI architectures across LLMs, prompt engineering, fine-tuning, GenAI SDKs, and multi-agent orchestration, while driving cloud-native solution design using distributed systems, microservices, Docker, Kubernetes, and Azure platforms such as AML, Cognitive Services, Databricks, and AKS.

Job Description of Role (RNR) :

As a Gen AI Lead, your primary role will be to design and develop advanced artificial intelligence solutions for various applications. You will work closely with cross-functional teams to understand business requirements and translate them into scalable and efficient AI architecture. You will also be responsible for leading the implementation and deployment of AI models and systems.

- Lead the design of architecture for generative AI solutions within the Azure ecosystem. Collaborate with project managers, data scientists, software engineers, and other stakeholders to understand business goals and determine AI requirements.

- Design and develop AI architectures, frameworks, and algorithms that can support large-scale and complex AI solutions.

- Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.

- Lead the development and implementation of AI models, ensuring adherence to best practices in machine learning and deep learning.

- Develop and maintain AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes.

- Optimize AI models and systems for performance, scalability, and efficiency.

- Conduct regular code reviews and provide technical guidance to junior members of the team.

- Stay up-to-date with the latest advancements in AI technologies, frameworks, and algorithms, and identify opportunities for their application in the organization.

- Collaborate with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments.

- Document AI architectures, design decisions, and technical specifications for reference and knowledge sharing.

- Leadership and Collaboration : Exceptional leadership skills with the ability to lead cross-functional teams and drive architectural decisions. Proven experience in mentoring junior team members, conducting code reviews, and fostering a culture of innovation and collaboration.

- Problem-solving and Innovation : Strong analytical and problem-solving skills, with a track record of proposing innovative solutions to complex technical challenges. Ability to stay updated on emerging AI technologies, best practices, and industry trends to drive continuous improvement.

Soft Skills/Other Skills :

- Communication Skills : Communicate effectively with internal and customer stakeholders. Communication approach : verbal, emails and instant messages.

- Interpersonal Skills : Strong interpersonal skills to build and maintain productive relationships with team members. Provide constructive feedback during code reviews and be open to receiving feedback on your own code.

- Problem-Solving and Analytical Thinking : Capability to troubleshoot and resolve issues efficiently. Analytical mindset.

- Task/Work Updates : Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps. Provides regular updates, proactive and due diligent to carry out responsibilities.

What Success Looks Like (6-12 Months) :

Within 6-12 months, the GenAI Technical Architect is expected to successfully design and deliver scalable, production-grade GenAI and Agentic AI solutions on Azure using LLMs, prompt engineering, fine-tuning, and multi-agent orchestration. Success includes establishing reusable architecture standards and improving scalability, reliability, and deployment efficiency through cloud-native technologies such as microservices, Docker, Kubernetes, and AKS, while enabling measurable business impact through enterprise AI adoption.

Secondary Skills (Good to have) :

- Security and Compliance : Understanding of security principles and best practices in AI development, with the ability to implement security controls, encryption mechanisms, and access management policies to protect AI models and sensitive data.

- Integration and Deployment : Proficiency in implementing CI/CD pipelines, automation scripts, and infrastructure as code (IaC) using tools such as Azure DevOps, Terraform, or Ansible. Experience in containerization and orchestration of AI workloads using Docker and Kubernetes.

- Software Development : Strong programming skills in languages such as Python, with experience in developing AI applications, RESTful APIs, and microservices architectures. Familiarity with software development methodologies such as Agile or Scrum.

- Communication and Presentation : Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Experience in preparing and delivering technical presentations, architecture diagrams, and documentation to communicate architectural decisions and design rationale effectively.

Why Join Us :

This is an opportunity to own and build next-generation AI systems from the ground up, combining development and architecture in a meaningful way. You will play a key role in shaping scalable AI solutions while working in a collaborative, innovation-driven environment.