Technical Architect, AI

Position Overview

The AI Technical Architect is responsible for designing, developing, and implementing advanced artificial intelligence solutions that address critical business challenges. The role demands a deep understanding of AI technologies, architecture principles, and hands-on experience in building scalable AI systems. The ideal candidate will collaborate with cross-functional teams to deliver innovative solutions, ensuring alignment with organisational goals and industry best practices.

Key Responsibilities

• Lead the design and architecture of AI-driven platforms, ensuring scalability, security, and performance.
• Collaborate with stakeholders to understand business requirements and translate them into AI solutions.
• Evaluate and select appropriate AI frameworks, tools, and technologies for various use cases.
• Oversee the development, deployment, and integration of machine learning models and AI services.
• Establish best practices for AI development, including data governance, model management, and MLOps processes.
• Mentor and guide technical teams in the adoption and implementation of AI technologies.
• Stay updated with the latest advancements in AI, machine learning, and data science, and recommend relevant innovations.
• Ensure compliance with regulatory requirements, data privacy, and ethical AI standards.
• Prepare technical documentation, architectural diagrams, and reports as required.

Qualifications and Skills

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field. A PhD is an added advantage.
• 10+ years of experience in software architecture, with at least 3 years in AI/ML solution design and implementation.
• Strong proficiency in one or more programming languages (Python, Java, R, etc.) relevant to AI development.
• Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.
• Expertise in cloud platforms (Azure, AWS, GCP) and containerisation (Docker, Kubernetes) is highly desirable.
• Excellent understanding of data engineering, model deployment, and MLOps pipelines.
• Strong analytical, problem-solving, and communication skills.
• Ability to work collaboratively in a multicultural and distributed team environment.

Preferred Attributes

• Relevant AI certifications (e.g., Microsoft Certified: Azure AI Engineer Associate, Google Professional Machine Learning Engineer).
• Experience in developing AI solutions for Indian or international markets.
• Demonstrated ability to manage multiple projects and priorities effectively.

Preferred Skills

• Experience with deep learning architectures (CNNs, RNNs, LSTMs, Transformers).
• Familiarity with MLOps and CI/CD pipelines for model deployment and monitoring.
• Understanding of ethical AI practices and data privacy regulations.
• Published research papers or contributions to open-source AI projects.
• LLM: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama.
• LLM Ops: ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI.
• Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery.
• Cloud Knowledge: AWS/Azure/GCP.
• Dev Ops (Knowledge): Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus.
• Cloud Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert.
• Proficient in Python, SQL, JavaScript.

Locations

Location: Bangalore, Karntaka, India

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.