AI Architect Quality Intelligence
AI Architect Quality Intelligence
Zensar TechnologiesEarly 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
Key Skills
Technical roadmap decisions
Trajectory grading
Fairness audits
Evaluation-driven development
Drift monitoring
Safety attestations
