Technical Architect

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