Principal Engineer - AI Architect / Principal Data Scientist

We are looking for a seasoned AI Architect / Principal Data Scientist to join our AI & Tech Accelerator. In this role, you will lead the design, architecture, and enterprise-scale deployment of advanced AI systems, leveraging Machine Learning, Generative AI, and emerging Agentic AI paradigms. You will play a critical role in shaping AI strategy, driving innovation at scale, and enabling business transformation through cutting-edge intelligent systems.

Key Responsibilities:

In this role, you will operate at the intersection of strategy, architecture, and execution, driving enterprise-wide AI adoption.

Architect & Scale AI Solutions:

Design end-to-end AI/ML architectures, including scalable, secure, and production-ready systems using Machine Learning, Deep Learning, and Large Language Models (LLMs). Establish best practices for building robust and reusable AI platforms.

Lead Generative & Agentic AI Innovation:

Define and implement enterprise-grade Generative AI and Agentic AI solutions, including multi-agent systems, autonomous workflows, and LLM orchestration frameworks. Drive innovation in areas such as RAG, context engineering, and intelligent automation.

Enterprise Impact & Transformation:

Own and deliver scalable AI solutions across multiple business domains (marketing, supply chain, retail, operations), ensuring measurable business impact and alignment with organizational strategy.

Technical Leadership & Governance:

Act as a technical authority defining architecture standards, AI governance, model lifecycle management, and responsible AI practices. Ensure scalability, security, and compliance across all AI initiatives.

Cross-functional Leadership:

Collaborate with senior stakeholders, product leaders, data engineers, and platform teams to translate business problems into AI-driven solutions. Lead architecture discussions and influence key technical decisions.

Mentorship & Capability Building:

Mentor senior engineers and data scientists, drive knowledge sharing, and build a strong AI engineering culture. Lead communities of practice and contribute to organizational capability development.

What We Are Looking For:

We are seeking a strategic thinker and hands-on architect who combines deep technical expertise with strong business acumen and leadership capabilities.

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field
• 11–13 years of experience in AI/ML, with significant experience in designing and deploying large-scale AI systems
• Proven experience in architecting enterprise-grade AI/ML platforms and solutions

Technical Expertise:

AI/ML & Advanced Analytics:

• Strong expertise in Machine Learning, Deep Learning, and statistical modeling
• Experience designing scalable ML systems and production pipelines

Generative AI & Agentic AI:

• Deep expertise in LLMs (GPT, Claude, Llama, Gemini) and their enterprise applications
• Strong experience in RAG architectures, prompt engineering, context engineering, embeddings, and vector databases
• Hands-on experience with agentic frameworks (LangGraph, CrewAI, AutoGen) and multi-agent orchestration

Architecture & Engineering:

• Strong system design and architecture skills for distributed AI systems
• Expertise in Python, SQL, and software engineering best practices
• Experience with microservices, APIs, and scalable backend systems

MLOps & Platform Engineering:

• Strong experience in MLOps practices including CI/CD, model versioning, monitoring, and governance
• Hands-on experience with tools such as MLflow, Vertex AI, Kubeflow, or similar

Cloud & Data Platforms:

• Deep experience with cloud platforms, especially GCP (Vertex AI, BigQuery) and/or Databricks
• Strong understanding of data lakes, data warehouses, and real-time data processing

Soft Skills & Mindset:

Strategic Leadership:

Ability to align AI initiatives with business goals and drive long-term technology vision

Ownership & Accountability:

Takes end-to-end ownership of architecture, delivery, and outcomes

Influence & Communication:

Strong ability to communicate complex technical concepts to senior stakeholders and executives

Innovation Mindset:

Continuously explores emerging AI trends and drives adoption of next-gen technologies

Additional Expectations (Architect Level):

• Define AI roadmap and contribute to organizational AI strategy
• Establish reusable frameworks, accelerators, and best practices
• Drive cost optimization and performance efficiency at scale
• Ensure ethical AI and responsible AI implementation