Aksha Jain

About Aksha Jain

Technical Project Manager (Engagement Manager) with hands-on experience delivering AI/ML, automation, and large-scale data engineering initiatives on Google Cloud. I partner with ML engineers, data scientists, backend and SRE teams to define technical scope, establish roadmaps, and run Agile execution that moves projects from prototype to production with governance and observability built in. What I bring: End-to-end delivery leadership: requirements, sprint and release planning, dependency and risk management, and stakeholder communication across multiple time zones. Technical fluency: familiar with Vertex AI, BigQuery, Dataflow, Airflow, Terraform, Kubernetes, and modern CI/CD practices — enabling pragmatic decisions that balance speed, cost, and reliability. Operational focus: collaborate with SRE and security teams to define runbooks, SLOs, monitoring, and secure deployments so models and automations perform in production. Process & people: drive standardized documentation, retrospectives, and knowledge transfer to raise team throughput and reduce onboarding time. Business outcomes orientation: translate technical delivery into measurable value — accelerating time-to-market for AI features, automating manual workflows to cut operational costs, improving model uptime and MTTR, and delivering better SLAs and customer experience. I thrive on bridging product goals and technical execution to deliver solutions that scale and show clear business impact.

Experience

1. Engagement Manager

   Zion Cloud Solutions

   Oct 2025 — Present · Hyderabad, IN

   As Engagement Manager for Google Cloud engagements, I run cross-functional delivery for AI/ML, automation, and large-scale data engineering initiatives. I work directly with ML engineers, data scientists, backend and infra teams to convert business objectives into technically sound, delivery-ready plans. My responsibilities include sprint and release management, roadmap creation, risk and dependency tracking, and stakeholder reporting. Key contributions: •Scoped and delivered cloud-native ML/AI solutions and enterprise automation workflows, ensuring smooth handoff from labs to production. •Implemented delivery governance (CI/CD pipelines, quality gates, runbooks) and championed best practices for model lifecycle, observability, and cost control. •Led sprint cadence, cross-team coordination, and vendor management across multiple time zones, keeping stakeholders aligned and informed. •Improved team efficiency through process improvements, standardized documentation, and regular knowledge transfer sessions. •Collaborated closely with SRE and security teams to meet operational SLOs, enforce security/compliance controls, and drive incident preparedness. Business impact: •Accelerated delivery and reduced time-to-market for priority AI features, enabling product teams to realize value faster and capture incremental revenue sooner. •Automated manual data-preparation and deployment tasks, decreasing operational costs and freeing up core FTEs for higher-value work. •Increased model uptime and stability in production, improving customer experience and reducing incident mean time to repair (MTTR). •Delivered measurable improvements to business KPIs — examples include higher throughput of automated decisions, faster case resolution for clients, and improved compliance posture leading to lower audit risk and cost.

Education

• Hindustan University

  Bachelor of Technology - BTech, Aeronautics/Aviation/Aerospace Science and Technology, General

  2012 — 2016

• Nanyang Technological University Singapore

  Master of Science - MS, Aerospace, Aeronautical and Astronautical/Space Engineering

  2017 — 2020

• Technical University of Munich

  Master of Science - MS, Aerospace, Aeronautical and Astronautical/Space Engineering

  2017 — 2020

Skills

• Leadership
• Public Speaking
• Microsoft Office
• Management
• Project Management
• Microsoft Word
• Customer Service
• Research
• Powerpoint
• Microsoft Excel