Sr Principal Architect IC

Teradata; Karnataka; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

Teradata is seeking a Sr. Principal Architect of Cloud Platform Engineering to lead the evolution of our cloud platform and AI-enabled services.

You will set the technical strategy across multi-cloud environments and architect scalable, secure infrastructure that enables autonomous AI workloads, with emphasis on performance, reliability, and cost control. You will guide engineering teams, shape platform primitives, and drive adoption of cloud-native patterns to support Teradata’s

Job description

Our Company

At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

What You'll Do

As Sr. Principal Architect of Cloud Platform Engineering, you will lead the evolution of Teradata's cloud deployment and platform technologies into the agentic era—designing and executing the technical strategy for a cloud platform engineered from the ground up to serve autonomous AI systems as first-class compute consumers. You will define long-term cloud architecture across AWS, Azure, and GCP with multi-tenant and single-tenant models, agent-driven execution frameworks, and infrastructure primitives that agentic systems require: sub-second APIs, persistent agent memory, agent-scoped identity, fine-grained cost controls, and deterministic audit trails. Your platform decisions will directly enable Teradata's engineering teams to adopt AI-native development practices where autonomous agents become core participants in software delivery, while your leadership directly impacts the ability to scale globally, onboard agentic applications to production reliably, and operate infrastructure serving both human users and agents with equal rigor.

What Success Looks Like

Success means delivering a highly automated, secure, and resilient cloud platform architected natively for autonomous AI systems and the engineering teams that deploy them: Sub-second agent API latencies; dynamic scaling for agent micro-queries; agent-driven provisioning and self-healing infrastructure; reliable agentic workload execution with <5% cost variance from workload unpredictability Identity and cost control systems that govern both human and agent actors; observable, debuggable agent execution; per execution cost tracking and circuit breaking; deterministic audit trails for agentic decision reasoning Engineering teams shipping features authored, tested, and reviewed by agentic systems; measurable velocity and quality improvements from autonomous coding agents; reduced manual toil in infrastructure management and code verification Reduced provisioning times; strong SLA adherence for both human and agent workloads; high platform availability (>99. 95%); optimized cloud spend with per-execution controls; incident response accelerated by agent-driven diagnostics and remediation.

Who You'll Work With

Lead and mentor teams across Platform Engineering, DevOps, and SRE on agentic-era infrastructure patterns and practices; Partner with Product, Security, Finance, AI/ML platform, and LLM framework teams to align infrastructure capabilities with both business and agentic workload requirements; Collaborate with cloud providers and internal architecture teams to drive consistency, innovation, and operational excellence at scale; Work with engineering leadership to establish AI-native development practices that depend on your platform primitives (agent identity, cost controls, observability); Report into senior engineering leadership, shaping Teradata's cloud, SaaS, and agentic platform strategy.

What Makes You a Qualified Candidate

Proven experience leading cloud platform, infrastructure, or SaaS engineering teams at scale, with deep expertise in cloud native architectures (serverless, event-driven, agent-driven execution models); Hands-on experience building and productionizing agentic applications at scale in production environments (agents writing code, managing infrastructure, making autonomous decisions), with deep familiarity in agentic frameworks (LangGraph, Claude API with tool_use, MCP servers, agent orchestration, memory management) and understanding how to architect infrastructure for their unique demands (sub-second latency, persistent memory, execution cost controls); Proven ability to architect for agentic workload patterns: understanding agent failure modes (hallucinations, cost drift, goal misalignment) and designing guardrails, observability, cost controls, and deterministic audit trails into platform primitives; balancing reliability, performance, security, and cost across diverse workloads from bulk analytical scans to high-frequencyagent micro-queries.

What You'll Bring

Direct, hands-on experience building systems where autonomous agents operate as core decision-makers and infrastructure consumers (not just code-assist tools); deep understanding of LLM capabilities and limitations in production—token budgets, latency requirements, hallucination handling, determinism, reproducibility, cost predictability; Ability to architect for agent auditability and debugging: designing systems that produce interpretable agent reasoning trails, enable reasoning replay, and establish accountability for agentic decisions; financial acumen for agent compute optimization—understanding per-execution spend tracking, cost circuit breaking, and the unique cost profiles of agentic vs. traditional workloads; Hands-on leadership experience with AWS, Azure, and/or GCP at scale; expertise in IaC, CI/CD, and platform automation (Terraform, Jenkins, GitHub Actions, deployment orchestration); strong understanding of observability, incident management, DR, and SLA-driven operations extended to non-deterministic agent workloads; A security-first mindset embedding IAM, agent identity, delegated authority, and intent-scoped governance into platform design; ability to define KPIs across deployment frequency, provisioning time, latency, error rates, infrastructure efficiency, agent execution cost per task, and agentic system reliability; Demonstrated success building and scaling high-performing teams through periods of significant technical and organizational change; proven ability to guide engineering teams on agentic thinking—shifting from "AI as tool" to "AI as engineer"—with corresponding trust, autonomy, and verification frameworks; Ability to articulate the transition to agentic infrastructure across technical and non-technical audiences; comfort with pioneering new patterns where agentic infrastructure is nascent and requires novel solutions for cost control, identity, latency, and auditability.

WHY THIS ROLE MATTERS

Agentic systems are moving from research labs into production. Cloud platforms not designed for agent workloads will struggle with their unique demands: sub-millisecond latency sensitivity, unpredictable concurrency, deterministic auditability, and per-execution cost transparency. Teradata has the opportunity to lead by building a cloud platform architected natively for the agentic era. This means infrastructure primitives designed from day one for agent identity, memory, cost controls, and reasoning auditability. It means engineering practices where autonomous agents become first-class team members in software delivery. The person in this seat will define what it means to operate cloud infrastructure in the age of agentic compute—setting the technical and operational standards that enable Teradata to scale AI-native engineering practices and reliably productionize agentic applications at scale.

Why We Think You'll Love Teradata

We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement. It is a deep commitment to doing the work to foster an equitable environment that celebrates people for all of who they are. Teradata invites all identities and backgrounds in the workplace. We work with deliberation and intent to ensure we are cultivating collaboration and inclusivity across our global organization. We are proud to be an equal opportunity and affirmative action employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status.