Technical Architect – AI & Gen AI Specialization

About the Role

Technical Architect - AI & GenAI Specialization

Key Responsibilities

Architecture Development

• AI architecture

• integrate with existing enterprise systems

• data privacy regulations (GDPR, CCPA, etc.)

Technical Leadership & Innovation

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

• drive innovation in AI-driven automation, personalization, and optimization

AI Model Development & Optimization

• training, fine-tuning, and deployment

• techniques such as prompt engineering, retrieval-augmented generation (RAG), and knowledge distillation

• MLOps and AIOps

Cloud & Infrastructure Integration

• Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI services

• cloud-native, containerized (Docker, Kubernetes), and scalable

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

Cross-Functional Collaboration

• engineering, data science, product, and business teams

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

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

Security, Compliance & Responsible AI

• ethical AI principles, bias mitigation, and fairness

• AI governance frameworks

• AI hallucinations, adversarial attacks, and regulatory compliance

Qualifications

Educational qualification:

Experience :

Mandatory/requires Skills :

• Strong hands-on experience

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

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

• AI-driven knowledge management, summarization, and automation

Software Architecture & Engineering

• enterprise software architectures, microservices, APIs, and distributed computing

• Python, Java, Go, or other relevant languages

• GraphQL, REST APIs, and event-driven architectures

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

Cloud & DevOps

• Azure, AWS, or Google Cloud

• serverless AI architecture, Kubernetes, and cloud-native AI

• data engineering, data lakes, and streaming analytics for AI

Preferred Skills :

• translate complex AI concepts

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

Additional Information

Why Join Us

• enterprise-wide AI initiatives

• state-of-the-art AI technologies

• Competitive compensation, benefits, and career growth opportunities.

• innovation, collaboration, and continuous learning

apply now!