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AI Architect Quality Intelligence

AI Architect Quality Intelligence

Zensar Technologies
15-17 Years
Not Disclosed
Early Applicant
  • Posted a month ago
  • Be among the first 10 applicants

Job Description

What You Will Do

Experience Range - 15 Yrs +

  • Architect and evolve the platform suite
  • Design and refine the archetype-specific assurance lifecycles
  • Keep the platforms LLM-agnostic and deployable on any client stack — on-prem, cloud or hybrid — as model-mixing and constant provider churn become the market norm.
  • Own technical roadmap decisions for accelerators such as the Agentic Foundry (a 25-blueprint reference matrix) and the curated, swap-ready tooling ecosystem around each archetype.

Lead Evaluation-Driven Development

  • Build and govern eval suites — ground-truth Q&A sets, LLM-as-judge rubrics, frozen baselines — that gate every release rather than validate it after the fact.
  • Own trajectory grading, red/purple/blue-team probes and safety attestations for agentic and generative systems, and drift monitoring and fairness audits for classical ML.
  • Translate evaluation results into release decisions: eval-threshold gates, red-team severity floors, canary and shadow deployments, and rollback rehearsals.
  • Bring evaluation-driven development practice into client engagements — showing, not just telling, how a live harness beats a one-time audit.

Own Presales and Client Proposals

  • Respond to RFPs, RFIs and client proposals across both engines, translating client requirements into a defensible solution architecture and commercial structure.
  • Architect engagements across the full ladder — AI QA Assessment, AI QA Transformation, Managed AI QA — and fast-starts such as the LLM Health Check, Agent Stress Test and Compliance Sprint.
  • Build estimates, staffing plans and technical win themes that hold up under client and internal scrutiny, across client-managed, risk-reward and Zensar-managed commercial models.

Present and Articulate Value to Clients

  • Lead client workshops and technical walkthroughs, including guiding a CIO through the Agentic Foundry in a single session.
  • Build and deliver executive trust scorecards and portfolio risk heat maps that make the assurance story board-ready.

Build Practice IP and Mentor the Next Generation

  • Contribute reusable accelerators, reference architectures and industry packs across BFSI, TMT, and Manufacturing & Retail back into the practice's IP base.
  • Mentor and help build out the practice's emerging AI-specialist roles — Prompt Engineer, LLM-Eval Engineer, Agent Architect, Trajectory Eval Engineer, Knowledge/RAG Engineer, AI Security Analyst and Adversarial Red/Blue Team Lead.

More Info

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Key Skills

Technical roadmap decisions

Trajectory grading

Fairness audits

Evaluation-driven development

Drift monitoring

Safety attestations

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