Technical Architect

Job Description

About the Role

We are seeking a highly skilled and Technical Architect – AI & GenAI Specialization for design and implementation of cutting-edge AI-driven enterprise solutions. This role requires deep expertise in Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), Machine Learning (ML), and Cloud AI services.

Key Responsibilities

Architecture Development

• Define and implement AI architecture for enterprise applications.

• Develop AI frameworks and models that integrate with existing enterprise systems.

• Ensure AI solutions are scalable, secure, and compliant with data privacy regulations (GDPR, CCPA, etc.).

Technical Leadership & Innovation

• Architect AI-powered platforms that support Gen-AI & AI frameworks and models.

• Stay ahead of AI advancements and drive innovation in AI-driven automation, personalization, and optimization.

AI Model Development & Optimization

• Execute the training, fine-tuning, and deployment of LLMs and ML models.

• Optimize model performance using techniques such as prompt engineering, retrieval-augmented generation (RAG), and knowledge distillation.

• Implement MLOps and AIOps best practices for continuous model monitoring and improvement.

Cloud & Infrastructure Integration

• Design and deploy AI solutions on Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI services.

• Ensure AI applications are cloud-native, containerized (Docker, Kubernetes), and scalable.

• Implement data pipelines, feature stores, and vector databases for efficient AI processing.

Cross-Functional Collaboration

• Work closely with engineering, data science, product, and business teams to align AI initiatives with company goals.

• Provide technical mentorship and guidance to AI engineers and developers.

• Communicate AI strategy and roadmaps to senior leadership and stakeholders.

Security, Compliance & Responsible AI

• Ensure AI solutions adhere to ethical AI principles, bias mitigation, and fairness.

• Implement AI governance frameworks for explainability, accountability, and security.

• Address risks related to AI hallucinations, adversarial attacks, and regulatory compliance.

Qualifications

Educational qualification: B-Tech / M-Tech Computer Science preferred

Experience : 10+ Years

Mandatory/requires Skills :
Core AI & GenAI Expertise

• Strong hands-on experience with LLMs (GPT, Llama, Claude, etc.), ML frameworks (TensorFlow, PyTorch, Hugging Face), and deep learning models.

• Expertise in GenAI applications, including chatbots, code generation, multimodal AI, and synthetic data generation.

• Experience with RAG, vector databases (FAISS, Pinecone, Weaviate), and embeddings.

• Proficiency in AI-driven knowledge management, summarization, and automation.

Software Architecture & Engineering

• Strong understanding of enterprise software architectures, microservices, APIs, and distributed computing.

• Hands-on experience with Python, Java, Go, or other relevant languages.

• Familiarity with GraphQL, REST APIs, and event-driven architectures.

• Experience with MLOps pipelines, CI/CD for AI, and automated AI workflows.

Cloud & DevOps

• Expertise in deploying AI models on Azure, AWS, or Google Cloud.

• Experience with serverless AI architecture, Kubernetes, and cloud-native AI.

• Knowledge of data engineering, data lakes, and streaming analytics for AI.

Preferred Skills :

Leadership & Communication

• Ability to translate complex AI concepts into business-friendly insights.

• Strong stakeholder management, presentation, and decision-making skills.