Lead AI/ML Engineer

About the Role:

We are looking for a visionary AI/ML Lead to own our end-to-end artificial intelligence strategy and execution. This role will bridge cutting-edge research and real-world product impact by leading cross-functional teams of engineers, data scientists, and product stakeholders to build AI systems that are intelligent, reliable, scalable, and responsible.

Key Responsibilities

• Define and drive the AI roadmap across generative AI, agentic workflows, multimodal systems, and LLM-powered enterprise products.
• Lead, mentor, and grow a high-performing team of AI/ML engineers, prompt engineers, and applied scientists.
• Design and oversee the full AI lifecycle including problem framing, data strategy, feature engineering, model development, evaluation, deployment, and production monitoring.
• Architect multi-agent systems and AI pipelines using frameworks such as LangGraph, AutoGen, CrewAI, or equivalent orchestration tools.
• Collaborate with product, engineering, and business teams to embed AI capabilities into core user workflows, internal platforms, and client-facing solutions.
• Champion responsible AI by defining governance frameworks, evaluation standards, model guardrails, bias mitigation practices, and secure deployment standards.
• Drive adoption of MLOps and LLMOps practices including CI/CD, observability, model evaluation, prompt version control, and continuous improvement.
• Stay ahead of advancements in foundation models, applied AI frameworks, and enterprise AI architecture, converting innovation into practical business offerings.
• Partner with leadership teams and clients to identify high-value AI opportunities and translate them into scalable solutions and delivery roadmaps.

Required Skills and Experience

• 9+ years of experience in Data Science, Machine Learning, AI Engineering, or advanced analytics roles.
• Strong proficiency in Python for machine learning, model development, data engineering, and AI application development.
• Proven hands-on experience in ML model development, evaluation, deployment, and production support.
• Strong experience with Apache Kafka and streaming data processing.
• Deep understanding of feature engineering, model evaluation, experimentation, and production ML workflows.
• Strong working knowledge of SQL and large-scale data processing environments.
• Experience with AWS services and cloud-native ML tooling, including deployment and monitoring patterns.
• Hands-on experience with Snowflake and Snowpark for scalable enterprise data workflows.
• Experience building CI/CD pipelines and deployment automation for AI/ML systems.
• Hands-on experience with Terraform and infrastructure-as-code practices for cloud infrastructure management.

Preferred Qualifications

• Experience with Generative AI, LLM applications, RAG architectures, agentic AI systems, and prompt engineering.
• Exposure to multimodal AI solutions, conversational AI, and enterprise workflow automation.
• Experience in consulting-led delivery environments and working with global enterprise clients.
• Strong people leadership, stakeholder management, and solution consulting skills.