We are seeking a visionary and highly skilled AI Architect to join our leadership team. This pivotal role will be responsible for defining and implementing the end-to-end architecture for deploying our machine learning models, including advanced Generative AI and LLM solutions, into production. You will lead and mentor a talented cross-functional team of Data Scientists, Backend Developers, and DevOps Engineers, fostering a culture of innovation, technical excellence, and operational efficiency.
Office 2305, Yamuna Building Technopark Phase-III Campus, Trivandrum, Kerala , 695583
AI Architect- Immediate Requirement
Brief Description
Preferred Skills
Key responsibilities:
Architectural Leadership:
Design, develop, and own the scalable, secure, and reliable end-to-end architecture for deploying and serving ML models, with a strong focus on real-time inference and high availability.
Lead the strategy and implementation of the in-house API wrapper infrastructure for exposing ML models to internal and external customers.
Define architectural patterns, best practices, and governance for MLOps, ensuring robust CI/CD pipelines, model versioning, monitoring, and automated retraining.
Evaluate and select the optimal technology stack (cloud services, open-source frameworks, tools) for our ML serving infrastructure, balancing performance, cost, and maintainability.
Team Leadership & Mentorship:
Lead, mentor, and inspire a diverse team of Data Scientists, Backend Developers, and DevOps Engineers, guiding them through complex architectural decisions and technical challenges.
Foster a collaborative environment that encourages knowledge sharing, continuous learning, and innovation across teams.
Drive technical excellence, code quality, and adherence to engineering best practices within the teams.
Generative AI & LLM Expertise:
Architect and implement solutions for deploying Large Language Models (LLMs), including strategies for efficient inference, prompt engineering, and context management.
Drive the adoption and integration of techniques like Retrieval Augmented Generation (RAG) to enhance LLM capabilities with proprietary and up-to-date information.
Develop strategies for fine-tuning LLMs for specific downstream tasks and domain adaptation, ensuring efficient data pipelines and experimentation frameworks.
Stay abreast of the latest advancements in AI, particularly in Generative AI, foundation models, and emerging MLOps tools, and evaluate their applicability to our business needs.
Collaboration & Cross-Functional Impact:
Collaborate closely with Data Scientists to understand model requirements, optimize models for production, and integrate them seamlessly into the serving infrastructure.
Partner with Backend Developers to build robust, secure, and performant APIs that consume and serve ML predictions.
Work hand-in-hand with DevOps Engineers to automate deployment, monitoring, scaling, and operational excellence of the AI infrastructure.
Communicate complex technical concepts and architectural decisions effectively to both technical and non-technical stakeholders.
Requirements (Qualifications/Experience/Competencies)
Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related quantitative field.
Experience:
10+ years of progressive experience in software engineering, with at least 5+ years in an Architect or Lead role.
Proven experience leading and mentoring cross-functional engineering teams (Data Scientists, Backend Developers, DevOps).
Demonstrated experience in designing, building, and deploying scalable, production-grade ML model serving infrastructure from the ground up.
Technical Skills:
Deep expertise in MLOps principles and practices, including model versioning, serving, monitoring, and CI/CD for ML.
Strong proficiency in Python and experience with relevant web frameworks (e.g., FastAPI, Flask) for API development.
Expertise in containerization technologies (Docker) and container orchestration (Kubernetes) for large-scale deployments.
Hands-on experience with at least one major cloud platform (AWS, Google Cloud, Azure) and their AI/ML services (e.g., SageMaker, Vertex AI, Azure ML).
Demonstrable experience with Large Language Models (LLMs), including deployment patterns, prompt engineering, and fine-tuning methodologies.
Practical experience implementing and optimizing Retrieval Augmented Generation (RAG) systems.
Familiarity with distributed systems, microservices architecture, and API design best practices.
Experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack, Datadog).
Knowledge of infrastructure as code (IaC) tools (e.g., Terraform, CloudFormation).
Leadership & Soft Skills:
Exceptional leadership, mentorship, and team-building abilities.
Strong analytical and problem-solving skills, with a track record of driving complex technical initiatives to completion.
Excellent communication (verbal and written) and interpersonal skills, with the ability to articulate technical concepts to diverse audiences.
Strategic thinker with the ability to align technical solutions with business objectives.
Proactive, self-driven, and continuously learning mindset.
Bonus Points:
Experience with specific ML serving frameworks like BentoML, KServe/KFServing, TensorFlow Serving, TorchServe, or NVIDIA Triton Inference Server.
Contributions to open-source MLOps or AI projects.
Experience with data governance, data security, and compliance in an AI context.
All applications are to be sent by clicking the following link in our website.
https://www.timesworld.com/careers/ai-architect