AI Architect

Project description

We are seeking a seasoned AI Architect with a strong background in enterprise scale AI, Machine Learning, and Generative AI systems. This role is ideal for someone who combines deep technical expertise with strategic vision-someone who can define the AI roadmap, architect complex LLM driven solutions, and guide engineering teams in building secure, scalable, and production ready AI platforms. You should bring at least 7+ years of experience in IT, including hands on work with modern AI/ML technologies, cloud platforms, and enterprise architecture patterns.

Responsibilities

• Define and lead the enterprise AI & Generative AI strategy, including long term architecture roadmaps.
• Design end to end AI/ML and GenAI systems, covering data ingestion, feature engineering, model training, fine tuning, deployment, and monitoring.
• Architect LLM based solutions, including Retrieval Augmented Generation (RAG), prompt engineering frameworks, vector databases, and multimodal pipelines.
• Evaluate, fine tune, and deploy foundation models and LLMs for diverse business use cases.
• Build secure, scalable, high performance AI infrastructure on AWS, Azure, or GCP.
• Establish MLOps and LLMOps practices: CI/CD for models, model versioning, evaluation pipelines, observability, and automated testing.
• Implement Responsible AI, governance, data privacy, and security best practices across all AI and GenAI systems.
• Integrate AI/GenAI capabilities into enterprise applications, APIs, and microservices.
• Define evaluation frameworks for LLM performance, including hallucination detection, grounding, bias mitigation, and quality metrics.
• Optimize AI workloads for scalability, latency, and cost efficiency.
• Mentor AI/ML engineers, lead architecture reviews, and drive technical standards across teams.
• Stay current with advancements in LLMs, multimodal AI, vector search, and emerging generative technologies.

SKILLS Must have

• 7+ years of experience in IT, including at least 3-5 years in AI/ML architecture or senior technical leadership roles.
• Proven experience designing and deploying AI/ML and Generative AI systems in production.
• Strong understanding of LLMs, RAG architectures, vector databases, and prompt engineering.
• Hands on experience with cloud platforms (AWS, Azure, or GCP) and cloud native AI services.
• Expertise in MLOps/LLMOps tools and practices (CI/CD, model registries, monitoring, evaluation).
• Solid knowledge of Python, ML frameworks (PyTorch, TensorFlow), and modern data engineering tools.
• Experience with Responsible AI, governance frameworks, and enterprise grade security.
• Ability to translate business needs into scalable AI architectures and technical roadmaps.
• Strong communication skills and the ability to guide engineering teams and stakeholders.

Nice to have

n/a