Technical Project Manager

Technical Project Manager

Job description:
We are seeking a high-performing, deeply technical, and exceptionally self-reliant Technical Delivery Lead to drive the execution of core automation and artificial intelligence initiatives within our Application Infrastructure and Operations (AIO) team. Acting as a Technical Lead, this hands-on, high-impact position requires a strong technical baseline combined with master-level stakeholder management. The ideal candidate will operate with high autonomy, orchestrating multiple cross-functional teams using DevOps and Site Reliability Engineering (SRE) principles. You will own the day-to-day coordination, milestone tracking, and operational delivery of critical AI, vulnerability mitigation, and infrastructure automation streams, ensuring leadership is updated with strategic, high-level visibility.

Essential Duties & Responsibilities:

Orchestrate "Ask Oppy" Delivery: Serve as the primary operational driver for "Ask Oppy" our Agentic AIOps Orchestrator managing timelines, cross-team dependencies, integration of developed code blocks, and delivery milestones utilizing Google Cloud Vertex AI and Model Context Protocol frameworks.

Drive Core Automation & Self-Healing Solutions: Directly oversee and unblock critical cross-team infrastructure operations programs, including end-to-end password reset automation initiatives and Dynatrace monitoring, alerting, and self-healing automation workflows.

Advance I&O AI Initiatives: Manage execution timelines for specific Infrastructure and Operations (I&O) AI projects, aligning engineering output with broader organizational goals to ensure system resilience and reduce user impact.

Observability & Pipeline Standardization: Design, implement, and automate CI/CD pipeline guardrails and observability standards across multi-cloud environments using enterprise tools like Dynatrace, Splunk, and Cloudwatch to proactively prevent downtime.

System Testing, Validation & ETL Oversight: Define, organize, and execute end-to-end performance testing and data integrity validation, including Snowflake and ETL pathways, ensuring newly configured technical solutions meet strict performance benchmarks prior to production launch.

Unified Support & Intake Integration: Lead the technical implementation and workflows for unified support systems, leveraging IT Service Management (ITSM), ITIL, and Lean frameworks to turn operational workflows into repeatable, automated ticketing and platform solutions.

Vulnerability Tracking & Security Solutions: Formulate, integrate, and deploy standardized vulnerability tracking workflows and automated remediation frameworks across the portfolio to ensure infrastructure systems meet strict enterprise security compliance.

Cross-Functional Orchestration: Harmonize diverse engineering, application support, and data teams; manage resource dependencies; navigate competing technical priorities; and drive strict accountability across separate technical units to meet consolidated timeline goals.

Autonomy & Communication: Establish highly efficient, concise reporting cadences for leadership. Anticipate bottlenecks, clear roadblocks independently, and distill complex, multi-team technical statuses into clear, actionable executive updates.

Education:
Master s degree preferred
Bachelor s degree in Computer Science, Information Technology, Systems Engineering, or a related field required.

Experience:
8+ years leading complex technical projects, product delivery, or cloud infrastructure rollouts within a global enterprise IT environment, with at least 2+ years leading AI/AIOps platform deployments.

Deep AI & Agentic Literacy: Mastery of AI concepts, including Large Language Models (LLMs), Agentic AI, multi-agent reasoning, tool-calling architectures, Retrieval-Augmented Generation (RAG), and the Model Context Protocol (MCP).

Observability & Cloud Baseline: Hands-on experience with enterprise monitoring platforms (e.g., Dynatrace, Splunk, CloudWatch), cloud environments (Google Cloud Platform, AWS), and CI/CD pipeline automation.

Systems Thinking & Governance: Proven ability to translate complex I&O environments into contextual schemas for AI consumption, paired with experience establishing guardrails for data security, AI safety, and compliance.

SRE & DevOps Mindset: Deep familiarity with Site Reliability Engineering (SRE) principles, automated testing, IaC, and data pipeline oversight (e.g., Snowflake/ETL validation).