AI Technical Architect

• Expectation from client: 80% hands on AI architect with 20% team management experience. This person is expected to discover AI Transformation projects and drive them to closure. Manage a small team of 3 -4 engineers based in India. (More details in JD)
  
• Number of Rounds: 3 (2 Technical - Internal Wipro and Client 1 Business)
  

Role overview

We are seeking a Technical Architect of AI Engineering to lead foundational infrastructure efforts and the end-to-end delivery of several concurrent AI initiatives. This is a practitioner-first leadership role for an exceptional builder who can combine deep engineering execution with programme leadership customer influence and team development.

You will spend approximately 80% of your time operating as an individual contributor (Hands On) shipping production code architecting systems and conducting rigorous peer reviews and 20% defining technical strategy mentoring elite AI researchers and engineers and strengthening delivery governance. The role is accountable for engineering excellence predictable execution and measurable business outcomes for both Wipro and its customers.

AI initiative portfolio

Agentic AI and autonomous workflow automation

GenAI-powered business process transformation

AI Engineering platforms and products

Machine Learning and Predictive Analytics solutions

Intelligent automation and decision-support systems

Traditional machine learning applications

Key responsibilities

System architecture & hands-on development

Write deploy and maintain production-grade AI systems custom evaluation pipelines and high-performance synthetic data generation engines.

Architect robust scalable agentic loops including ReAct patterns state machines and human-in-the-loop workflows.

Design systems that manage complex state use context efficiently and degrade gracefully in production.

Guide solution architecture and technology decisions for scalable secure and resilient AI systems.

Drive engineering excellence across development testing deployment monitoring and production support.

AI programme & delivery leadership

Own end-to-end delivery of multiple simultaneous AI/ML GenAI and Agentic AI programmes.

Define delivery strategy execution plans milestones governance processes and success metrics.

Drive project execution from discovery through production deployment and operationalisation.

Manage programme risks dependencies budget scope quality and schedule.

Establish delivery governance and reporting mechanisms across multiple customer engagements.

Ensure predictable delivery while maintaining engineering quality and innovation standards.

Drive adoption of best practices for AI Engineering MLOps LLMOps evaluation observability and Responsible AI.

Technical leadership & review

Enforce an exceptionally high engineering standard through rigorous code reviews and scalable architectural patterns.

Bridge the gap between open-ended research and robust software engineering.

Work closely with architects principal engineers data scientists researchers and platform teams on client side.

Review technical risks architecture decisions evaluation methodologies and implementation approaches.

Evaluate emerging AI technologies and identify opportunities for customer innovation.

Pioneer the integration of AI coding assistants and automation into CI/CD and engineering lifecycles to maximise velocity.

Customer & executive stakeholder management

Act as the primary delivery leader for senior customer stakeholders.

Partner with customer executives to define AI roadmaps and transformation initiatives.

Present programme updates business outcomes risks and mitigation plans to customer leadership.

Build trusted-adviser relationships with customer executives and key business stakeholders.

Engage regularly with Wipro delivery account sales and practice leadership.

Provide accurate executive-level reporting to both Wipro and customer organisations.

Team building & talent development

Build and lead high-performing multidisciplinary AI engineering teams.

Develop talent through hands-on mentoring peer review technical coaching and clear engineering standards.

Define the appropriate mix of engineers researchers data scientists architects and platform specialists for each initiative.

Create a culture of ownership experimentation learning and disciplined production delivery.

Strengthen technical capability succession and leadership depth across the team.

Required technical profile

Engineering leadership

Proven track record as a Principal AI Engineer Staff Engineer or highly technical Architect.

Direct experience shipping LLM-backed applications to production and managing latency context limits and model degradation.

Demonstrated experience leading complex concurrent AI programmes from discovery through deployment and operationalisation.

Ability to balance hands-on technical contribution with executive stakeholder management delivery governance and team leadership.

Advanced AI tooling

Deep practical expertise using AI-first development environments and coding assistants.

Power-user experience with tools such as Claude Code OpenAI Codex Cursor or Windsurf.

Strong understanding of context-window management across multi-file codebases.

Practical knowledge of MLOps LLMOps model evaluation observability and Responsible AI.

Core engineering

Elite-level proficiency in Python and/or TypeScript.

Deep familiarity with modern backend architecture containerisation using Docker orchestration and scalable data pipelines.

Strong intuition for evaluating AI models working with generative APIs and building resilient systems around non-deterministic outputs.

Required Skills:

AI Architect

Required Education:

Engineering