Technical Delivery Lead

Accountabilities:

• • Agentic AI & AIOps delivery: Orchestrate enterprise-wide Agentic AI and AIOps initiatives, tracking milestones, integrating developed code, and coordinating deployment of multi-agent reasoning systems, dynamic agent registries, and tool-calling interfaces.
  • AI platform integration: Support delivery involving Google Cloud Vertex AI, Model Context Protocol (MCP), agentic frameworks, and related AI technologies while ensuring initiatives remain aligned with technical and business objectives.
  • Observability and self-healing: Lead operational delivery for enterprise observability programs, overseeing telemetry ingestion, monitoring standardization, automated alerting, and self-healing workflows across multi-cloud environments.
  • Security remediation: Drive standardized vulnerability tracking and automated remediation frameworks across application and infrastructure portfolios to strengthen enterprise security and compliance.
  • Cross-functional orchestration: Coordinate engineering, application support, data, security, and other technical teams, managing dependencies, resources, competing priorities, and accountability against consolidated delivery timelines.
  • Performance and value tracking: Establish quantitative KPIs covering delivery health, token consumption, operational improvements, MTTR, automation outcomes, and financial savings.
  • Executive reporting: Build and maintain concise reporting frameworks that communicate delivery status, risks, operational improvements, and measurable business value to executive leadership.
  • Technical problem solving: Anticipate bottlenecks, remove technical roadblocks, and independently drive resolution across complex, multi-team initiatives.
  • Stakeholder communication: Translate sophisticated technical information into clear, actionable updates for both technical stakeholders and senior executives.

  Requirements:

  • Education: Bachelor’s degree in Computer Science, Information Technology, Systems Engineering, or a related technical discipline is required; a Master’s degree is preferred.
  • Experience: 8+ years leading complex technical projects, product delivery initiatives, or cloud infrastructure rollouts within global enterprise IT environments, including at least 2+ years leading AI or AIOps platform deployments.
  • AI expertise: Strong understanding of Large Language Models (LLMs), Agentic AI, multi-agent reasoning, tool-calling architectures, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP).
  • Cloud and monitoring: Hands-on experience with enterprise monitoring platforms such as Dynatrace, Splunk, or CloudWatch, as well as cloud environments including GCP and AWS.
  • Automation: Experience with CI/CD pipeline automation, Infrastructure as Code (IaC), automated testing, and modern cloud delivery practices.
  • Enterprise AI readiness: Ability to translate complex infrastructure and operations environments into contextual schemas suitable for AI consumption, while establishing appropriate data security, AI safety, and compliance guardrails.
  • SRE expertise: Deep familiarity with Site Reliability Engineering principles, observability, reliability practices, and operational automation.
  • Data pipelines: Experience overseeing data pipelines and validation processes, including technologies such as Snowflake and ETL workflows.
  • Leadership: Demonstrated ability to coordinate diverse technical teams, manage dependencies, resolve competing priorities, and maintain accountability across complex programs.
  • Communication: Exceptional executive communication and stakeholder management skills, with the ability to simplify complex technical topics and provide clear recommendations.
  • Adaptability: Comfortable working across internal and external teams, participating in video meetings, and working onsite at corporate or client locations when required.
  • Additional requirements: For roles involving business travel or event attendance, a valid driver’s license and acceptable driving record may be required, along with the ability to lift up to 25 lbs when necessary.

  Benefits:

  • Healthcare: Medical, dental, and vision coverage, along with disability insurance and additional benefit options.
  • Flexible spending: Flexible Spending Accounts for medical, transit, and dependent care expenses.
  • Health Savings Account: HSA paired with a low-cost high-deductible medical plan.
  • Life insurance: Employer-paid life insurance and AD&D coverage.
  • Retirement: 401(k) Safe Harbor retirement plan with employer matching and immediate vesting.
  • Inclusive workplace: A commitment to an open, respectful, and inclusive environment where employees are empowered to contribute and grow.
  • Professional impact: Opportunity to work on advanced enterprise initiatives involving AI, automation, cloud infrastructure, observability, and cybersecurity.
  • Flexibility and accommodations: Reasonable accommodations are available during employment and the recruitment process for qualified individuals who require support.