Teradata - Staff Software Engineer - Cloud & AI Platform

Job Description :

We are looking for an exceptional Staff Cloud & AI Platform Engineer to own and independently build a next-generation enterprise-scale deployment and orchestration platform.

This role goes far beyond traditional CI/CD or infrastructure automation - it sits at the intersection of distributed systems, control-plane architecture, SRE principles, and applied AI/agentic workflows.

Contribute to the design and implementation of a stateful deployment control plane that treats deployments as a continuous convergence problem.

Enable safe, resumable, deterministic, and SLO-governed rollouts across multi-cloud, on-prem, and customer environments.

Implement the practical application of AI agents in DevOps by embedding intelligent decision-making into deployment workflows.

Apply AI agents for anomaly detection, failure diagnosis, rollout control, and automated mitigation.

Ensure all AI-assisted workflows preserve correctness, determinism, and full auditability.

This is a high-impact individual contributor role requiring deep technical judgment, delivery ownership, and the ability to turn abstract design into production-grade systems.

Key Responsibilities :

• Design and implement a stateful deployment control plane with deterministic, resumable execution and rollback support.
• Build deployment workflows that reconcile desired vs. actual state using durable control loops.
• Support multi-cloud, on-prem, and customer environments with a single orchestration framework.
• Implement SLO-governed promotion gates, error-budget checks, and bounded retry policies.
• Enable deployment models including self-service, wave-based rollouts, blue-green, managed updates, and maintenance windows.
• Define declarative, extensible workflow schemas with explicit dependencies, retries, and rollback semantics.
• Integrate deployment orchestration with CI/CD systems, artifact manifests, entitlement services, and downstream execution systems.
• Embed AI-assisted decision logic into deployment workflows for anomaly detection, failure diagnosis, and rollout control.
• Ensure AI-driven actions remain deterministic, auditable, reversible, and policy-constrained.
• Develop infrastructure and automation frameworks using Terraform, Python, and cloud-native services.
• Embed observability and telemetry into workflows to drive automated validation, retries, and rollback decisions.
• Provide hands-on technical leadership, mentoring engineers and driving platform architecture across DevOps, SRE, and CloudOps teams.

Who You'll Work With :

This is an individual contributor role. You will collaborate with project team members and architects, and report to the Senior Engineering Manager.

What Makes You a Qualified Candidate :

• Bachelor's or Master's degree in computer science or related field.
• 8 years of hands-on experience in DevOps, platform engineering, cloud infrastructure, or distributed systems.
• Proven experience developing and implementation of stateful systems such as control planes, workflow engines, or orchestration platforms.
• Experience building or operating enterprise-scale deployment systems across multi-cloud, hybrid, or on-prem environments.
• Deep expertise in CI/CD, release engineering, and deployment strategies including wave-based, blue-green, and managed rollouts.
• Practical experience applying SRE principles such as SLOs, error budgets, promotion gates, and automated rollback.
• Strong programming skills in Python, with the ability to build long-running services and automation frameworks.
• Hands-on experience with Infrastructure as Code, preferably Terraform, and cloud-native services (AWS, Azure, and/or GCP).
• Experience integrating observability and telemetry (metrics, logs, traces) into automated systems for decision-making.
• Demonstrated experience building or integrating AI-assisted or agentic workflows into DevOps or operational systems.
• Ability to design safe, auditable, policy-constrained automation, especially when applying AI or autonomous decision logic.
• Strong technical judgment and communication skills, with experience leading architecture across teams as an individual contributor.