AI Engineering Lead/Architect
Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Sep 1, 2026. Zensar Technologies scores A on the Alion truth index.
Own end-to-end delivery of a $10M+ engineering portfolio across clients - on time, on budget, and to quality bar.
Lead platform build, modernisation, and custom application programmes natively on cloud, spanning .NET Full-Stack, Java Distributed Systems, Python stack etc.
Set and enforce engineering standards: architecture guardrails, code quality, DevSecOps, and release cadence across multi-team engagements.
Manage programme risk proactively - escalate early, resolve decisively, and keep clients informed throughout.
Embed AI tooling across the SDLC - from AI-assisted requirements and design through to automated testing, code generation, and incident response.
Architect and operationalise agentic systems and workflows that reduce manual toil, accelerate delivery cycles, and improve output quality.
Quantify the impact of AI adoption: establish baselines, track velocity and quality metrics, and present measurable efficiency gains to clients and leadership.
Stay ahead of the AI tooling curve; evaluate and pilot emerging platforms (LLM orchestration, RAG pipelines, AI code assistants).
Carry full P&L accountability for the portfolio - margin, revenue, forecasting, and commercial hygiene.
Partner with practice, consulting, and client partner leaders to identify expansion opportunities within existing accounts and shape new pursuit strategies.
Translate delivery track record into growth narrative - contribute to proposals, solution designs, and client presentations that differentiate on execution credibility.
Serve as the senior delivery point-of-contact for clients - build trust-based relationships at CTO/CIO/VP level.
Facilitate governance forums (steering committees, QBRs, escalation calls) with clarity and confidence.
Align internal stakeholders - practice heads, resource managers, people leaders - to programme needs without bureaucratic drag.
Lead, mentor, and grow a high-performing engineering organisation; foster a culture of ownership and continuous improvement.
Champion individual upskilling - create structured learning pathways around AI, cloud, and modern engineering practices.
Spot and develop next-generation delivery leaders from within the team.