We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization. You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value.
Roles & Responsibilities
- Technical Leadership
- Lead the technical design and architecture of complex Generative AI systems.
- Ensure solutions align with business objectives, scalability requirements, and technical feasibility.
- Guide development teams through best practices, architecture reviews, and technical decision-making processes.
- Solution Architecture
- Design and develop end-to-end Generative AI solutions, including data pipelines, model training, deployment, and real-time monitoring.
- Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments.
- Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks.
- Design, train, and fine-tune AI/ML models, especially Generative AI and Large Language Models (LLMs), to address specific use cases.
- Build conversational AI solutions and chatbots using frameworks such as LangChain, RAG (Retrieval-Augmented Generation), and Chain-of-Thought (COT) prompting.
- Production Deployment
- Lead the deployment of Generative AI models into production environments.
- Optimize deployment pipelines leveraging tools like Docker, Kubernetes, and cloud-native services for orchestration.
- Ensure seamless integration of GenAI solutions into existing CI/CD pipelines.
- Data Processing & Feature Engineering
- Build scalable ETL workflows for managing structured, semi-structured, and unstructured data.
- Implement data wrangling, preprocessing, and feature engineering pipelines to prepare data for Generative AI applications.
- Optimize workflows to extract meaningful insights from large datasets.
- Model Optimization
- Identify and implement optimization strategies such as hyperparameter tuning, feature engineering, and model selection for performance enhancement.
- Focus on computational efficiency and scaling models to production-level performance.
- Pilot/POCs Development
- Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements.
- Collaborate with delivery and product teams to scale successful pilots to production-grade solutions.
- Evangelization
- Promote and drive the adoption of Generative AI solutions across customer and delivery teams.
- Provide technical leadership and mentorship to teams working on GenAI projects.
- Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders.
- Continuous Improvement
- Stay at the forefront of AI advancements, frameworks, and tools, including emerging concepts in Generative AI.
- Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications.
Required Skills & Qualifications
- 10+ years of experience in AI/ML architecture, model development, and production deployment.
- Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions.
- Hands-on experience with frameworks like LangChain, Retrieval-Augmented Generation (RAG), and advanced prompting techniques.
- Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting.
- Experience working with cloud platforms, primarily GCP, with optional experience in AWS or Azure.
- Strong understanding of MLOps tools, pipelines, and model monitoring in production.
- Proficiency in Python and SQL for model development and data processing.
- Experience with data preprocessing, ETL workflows, and feature engineering for AI applications.
- Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes.
- Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions.
- Experience working with large datasets for structured and unstructured AI applications.
- Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies.
- Proven track record of leading POCs/pilots and scaling them to production-grade deployments.
Preferred Skills
- Familiarity with Reinforcement Learning from Human Feedback (RLHF).
- Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks.
- Strong understanding of orchestration for large-scale production environments.
Key Attributes
- Strong technical leadership and mentorship abilities.
- Excellent communication and stakeholder management skills.
- Strategic thinking with the ability to architect scalable and future-ready AI systems.
- Passion for solving business challenges using state-of-the-art AI techniques.
- Commitment to staying updated with the latest advancements in AI/ML technologies.
Why Join Us
- Lead the development of cutting-edge Generative AI solutions for real-world applications.
- Be part of a collaborative, innovative, and technology-driven team.
- Opportunity to work with advanced AI/ML tools and frameworks.
- Drive innovation through technical leadership, mentorship, and solution evangelization.
- Continuous professional growth with access to the latest AI/ML technologies and frameworks.
