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Principal AI Platform Architect

External
Unisys logoUnisys · Bangalore, India
Full-timeHybridToday
AgileAWSAzureCI/CDComplianceData Warehousing
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Responsibilities

  • Lead enterprise and solution architecture across complex, multi-stakeholder environments, from greenfield platforms to legacy transformation
  • Define and own API strategy, governance frameworks, and integration patterns at organisational level
  • Design and deliver on-prem, cloud-native and hybrid infrastructure across AWS, Azure and GCP with focus on scalability, cost, and compliance
  • Architect and operate AI/ML platforms including LLM pipelines, GPU infrastructure, and agentic orchestration
  • Establish DevSecOps practices including CI/CD, Infrastructure as Code, and automated deployment pipelines
  • Define data architecture, integration patterns, and analytics capability to support decision-making
  • Lead vendor evaluation, procurement, and technology selection, including AI and LLM tooling
  • Provide board-level advisory on technology strategy, digital transformation and risk
  • Build and mentor engineering teams and uplift capability through structured practices and frameworks
  • Own governance, security and compliance posture across regulatory and emerging AI frameworks
  • Technical Competencies
  • On-Prem, Cloud & Infrastructure: Dell AI Factory, AWS, Azure, GCP; Terraform; containerisation and CI/CD pipelines
  • AI/ML & LLM Operations: GPU infrastructure, model deployment, inference optimisation, agentic workflows
  • Security & Identity: SSO, OAuth2/OIDC, ISO27001, PCI DSS, GDPR, emerging AI regulation
  • APIs & Integration: REST, GraphQL, enterprise API governance
  • Data & Analytics: ETL, data warehousing, BI tooling, compliant data architecture
  • Frameworks & Methods: SAFe, Agile, Domain-Driven Design
  • Leadership & Impact
  • Operates at enterprise and board level
  • Shapes long-term platform and technology strategy
  • Balances innovation with risk, governance, and scalability
  • Drives organisational capability uplift
  • Experience Profile (Indicative)
  • Significant experience in enterprise architecture, platform engineering, or infrastructure leadership roles
  • Proven track record designing and delivering complex cloud, hybrid, and enterprise-scale platforms
  • Deep experience in defining architecture standards, governance models, and technology strategy
  • Strong background in AI/ML platforms, data architecture, and emerging technology adoption
  • Experience operating at senior stakeholder and board level, including advisory and decision support
  • Demonstrable leadership of engineering and architecture teams in complex, multi-stakeholder environments
  • Experience working within regulated environments with strong security, risk, and compliance requirements
  • Proven ability to balance innovation with operational stability, cost, and scalability.
  • #LI-ND1
  • You will be successful in this role if you have:
  • 12+ years of experience in software engineering, AI/ML systems, or platform architecture, with strong focus on Generative AI
  • Proven experience acting as Senior Principal / Enterprise Technical Architect within large Engineering organizations
  • Demonstrated ability to define architecture standards and guide large engineering teams
  • Strong stakeholder engagement skills across engineering leadership and executive teams
  • Self-driven, collaborative, and comfortable working in fast-paced engineering environments
  • Bachelor's or Master's degree in Computer Science, Engineering, AI, or related field
  • Cloud or AI certifications (Azure Developer, Azure AI Engineer, or equivalent) preferred
  • Local employment practices and rights may vary by jurisdiction and are subject to applicable local laws. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers.

Benefits

Parental leave

Additional Information

What success looks like in this role: Role Purpose Lead the design, build, and governance of enterprise-grade AI and cloud platforms Define scalable, secure, and compliant architecture across complex environments Enable AI capability at organisational level through infrastructure, standards, and strategy


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