AI Architect

Role Overview

We are seeking an exceptional AI Architect to lead the design, development, and delivery of enterprise AI solutions across traditional machine learning, generative AI, and agentic AI systems. This role demands a unique combination of deep technical expertise and strong leadership capabilities—you must be equally comfortable architecting complex AI platforms, rolling up your sleeves to code hands-on implementations, and engaging confidently with senior stakeholders to drive business outcomes.

The ideal candidate brings proven experience deploying ML models in commercial production environments, a sophisticated understanding of GenAI design patterns and evaluation frameworks, and the ability to translate cutting-edge AI developments into pragmatic, implementable solutions. You will drive technical teams to deliver on time while maintaining the learning mindset necessary to stay at the forefront of this rapidly evolving field, all while building strong client relationships through excellent communication and confident technical leadership.

Key Responsibilities

Technical Leadership & Architecture

• Design and architect end-to-end AI solutions spanning traditional ML, generative AI, and Agentic AI systems
• Evaluate and select appropriate design patterns for GenAI implementations, clearly articulating tradeoffs between approaches (RAG vs fine-tuning, prompt engineering strategies, agent orchestration patterns, etc.)
• Define and implement comprehensive evaluation frameworks for GenAI systems, including quality metrics, performance benchmarks, and responsible AI considerations
• Stay current with emerging AI/ML developments and assess their practical applicability to client environments
  
  

Client Engagement & Stakeholder Management

• Serve as trusted technical advisor to clients, translating complex AI concepts into business value
• Lead solution workshops and technical pre-sales presentations with C-level executives and technical teams
• Build and maintain strong client relationships through confident communication and delivery excellence
• Bridge the gap between cutting-edge AI capabilities and pragmatic, implementable solutions
  
  

Team Leadership & Delivery

• Drive technical teams to deliver high-quality AI solutions on time and within scope
• Provide hands-on technical guidance and code reviews, leading by example
• Manage delivery timelines and proactively identify and mitigate risks
• Mentor team members on AI best practices, design patterns, and implementation approaches
  
  

Hands-On Development

• Contribute directly to architecture and code implementation when needed
• Build proof-of-concepts and prototypes to validate technical approaches
• Debug complex technical issues across the AI stack
• Ensure code quality, scalability, and maintainability standards
  
  

Minimum Qualifications

Required Qualifications

• 8+ years of experience in AI/ML engineering and architecture
• Proven track record of implementing ML models in commercial production environments
• Deep expertise in traditional machine learning (supervised/unsupervised learning, feature engineering, model optimization)
• Significant experience with Generative AI technologies (LLMs, prompt engineering, RAG, fine-tuning, vector databases)
• Hands-on experience building agentic AI systems and multi-agent architectures
• Strong programming skills in Python and relevant ML/AI frameworks (SKlearn, XGBoost, PyTorch, TensorFlow, LangChain, LlamaIndex, etc.)
• Demonstrated ability to design and implement GenAI evaluation
• Excellent communication skills with ability to present complex technical topics clearly to both technical and non-technical audiences
• Strong project management capabilities with history of delivering complex projects on schedule
  
  

Preferred Qualifications

• Experience with enterprise AI platform development and MLOps practices
• Knowledge of AI governance frameworks and responsible AI practices
• Familiarity with cloud platforms (AWS, Azure, GCP) and their AI/ML services
• Experience with real-time AI systems and low-latency architectures
• Background in telecommunications, financial services, or other regulated industries
• Advanced degree in Computer Science, AI/ML, or related technical field
  
  

Key Competencies

• Technical Excellence
  
  

Expert understanding of GenAI design pattern tradeoffs (RAG architectures, agent frameworks, tool use, memory systems)

Proficiency in GenAI evaluation methodologies (automated metrics, LLM-as-judge, human evaluation)

Strong foundation in traditional ML fundamentals and deployment patterns

• Leadership & Delivery
  
  

Ability to drive teams toward concrete deliverables while maintaining quality standards

Experience managing multiple stakeholders and competing priorities

Track record of delivering complex technical projects in client environments

• Communication & Influence
  
  

Confident, clear communication style suitable for executive engagement

Ability to build credibility quickly with technical and business stakeholders

Skill in translating technical complexity into actionable business insights

• Mindset & Approach
  
  

Continuous learning orientation with pulse on latest AI developments

Pragmatic decision-making that balances innovation with implementability

Client-centric mindset focused on delivering measurable business value

Comfortable with ambiguity and able to structure unstructured problems

What Success Looks Like

• Successful delivery of high-impact AI solutions that drive measurable business outcomes
• Strong client satisfaction and repeat engagement opportunities
• Team members who are growing technically and delivering high-quality work
• Solutions that are maintainable, scalable, and aligned with industry best practices
• Recognition as a trusted technical advisor within client organizations

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