AI Architect

Role Overview:

We are seeking an experienced AI Architect who can lead end-to-end AI solutioning, from business problem framing to architecture design and implementation guidance. This role requires a blend of technical depth, strategic thinking, and stakeholder engagement to design scalable, secure, and business-aligned AI/ML solutions.

Key Responsibilities:

1. AI Solutioning & Architecture

• Translate business requirements into AI-driven solution architectures
• Design end-to-end systems including data pipelines, model development, deployment, and monitoring
• Define reference architectures, reusable frameworks, and best practices

2. Stakeholder Engagement

• Collaborate with business leaders, product managers, and engineering teams to identify AI opportunities
• Act as a trusted advisor, explaining AI capabilities, trade-offs, and ROI
• Lead solution workshops, PoCs, and technical discussions

3. Technology Leadership

• Select appropriate tools, platforms, and frameworks (e.g., TensorFlow, PyTorch, cloud AI services)
• Architect solutions leveraging cloud platforms (AWS / Azure / GCP) and modern data stacks
• Ensure scalability, reliability, and performance of AI systems

4. Governance & Responsible AI

• Define and enforce AI governance, ethics, and compliance standards
• Ensure solutions adhere to security, privacy, and regulatory requirements
• Implement model explainability, bias detection, and monitoring mechanisms

5. Delivery Oversight

• Guide development teams through implementation
• Review code, models, and architectures to ensure quality
• Drive PoCs to production-ready solutions

Required Qualifications:

• Bachelor’s/Master’s degree in Computer Science, AI, Data Science, or related field
• 10+ years of experience in technology, with 5+ years in AI/ML architecture or solutioning
• Strong experience in:
• Machine Learning, Deep Learning, NLP, or Generative AI
• Designing distributed and scalable systems
• API-first and microservices architecture
• Hands-on experience with:
• Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• MLOps tools (MLflow, Kubeflow, SageMaker, etc.)
• Data platforms (Spark, Databricks, Snowflake)

Preferred Skills:

• Experience in Generative AI / LLM-based solutions
• Knowledge of RAG architectures, prompt engineering, vector databases
• Familiarity with DevOps / MLOps pipelines
• Experience in regulated industries (Banking, Healthcare, etc.)
• Strong communication and presentation skills

Key Competencies:

• Solution-oriented mindset
• Strategic thinking with hands-on execution ability
• Strong problem-solving and analytical skills
• Ability to influence senior stakeholders