Senior Engineering Manager – Delivery

XenonStack is the fastest-growing Data and AI Foundry for Agentic Systems , enabling enterprises to design, deploy, and scale AI agents that deliver measurable business outcomes.

We build enterprise-grade platforms across the agentic stack:

ElixirData – Context OS for Agentic Intelligence A unified context layer powering memory, reasoning, grounding, and decision intelligence for AI agents across complex enterprise workflows.

NexaStack AI – Agentic Infrastructure Automation Platform A cloud-native platform for deploying, operating, observing, and scaling agentic workloads, inference pipelines, and AI infrastructure with security, reliability, and efficiency.

Akira AI – Agentic AI Platform An enterprise platform for building, orchestrating, governing, and operating AI agents that automate real-world business processes at scale.

Our mission is to accelerate the world’s transition to AI + Human Intelligence by making agentic systems reliable, responsible, and enterprise-ready .

We are seeking a Senior Engineering Manager – Delivery to own end-to-end product delivery execution across our Agentic AI platforms.

This role is accountable for predictable releases, delivery rigor, and production stability , orchestrating execution across Product, AI Engineering, and AI Quality & Reliability —without owning architecture, product prioritization, or quality standards.

If you excel at execution leadership, delivery discipline, and cross-functional alignment , this role is designed for you.

Ensure that what is committed gets delivered —on time, with confidence, and with minimal rework—while continuously improving delivery velocity, stability, and execution maturity.

Own delivery execution from commitment → release → post-release stabilization .

Drive delivery planning, sequencing, and dependency management across teams.

Ensure delivery plans are realistic, transparent, and accountable.

Lead release planning, cut decisions, and timelines across multiple teams.

Coordinate cross-platform releases and resolve inter-team dependencies.

Own release calendars, communication plans, and stakeholder updates.

Own delivery predictability across scope, timelines, and confidence.

Identify risks early and proactively drive mitigation plans.

Ensure no last-minute surprises for leadership or customers.

Co-own release readiness decisions with the Head of AI Quality & Reliability .

Ensure scope completeness, known risk visibility, rollback readiness, and monitoring plans.

Provide final delivery readiness recommendations.

Act as the delivery integrator across: Product Management (what & why) AI Engineering (how) AI Quality & Reliability (confidence & correctness)

Product Management (what & why)

AI Engineering (how)

AI Quality & Reliability (confidence & correctness)

Resolve execution friction and unblock teams proactively.

Lead and mentor delivery-focused Engineering Managers and Program Leads.

Build a culture of ownership, urgency, and execution excellence .

Drive performance management and career development for delivery roles.

Own and report delivery KPIs, including: On-time delivery Escaped defects Rework rate Release stability Cycle time and throughput

On-time delivery

Escaped defects

Rework rate

Release stability

Cycle time and throughput

Use metrics to improve systems and processes—not to assign blame.

Champion AI adoption across delivery workflows: AI-assisted planning and estimation Automated readiness and release checks Intelligent risk detection

AI-assisted planning and estimation

Automated readiness and release checks

Intelligent risk detection

Partner with AgentOps and tooling teams to continuously improve delivery velocity and quality.

Experience delivering AI/ML or platform products .

Familiarity with cloud-native architectures and DevOps practices .

Exposure to enterprise domains such as BFSI, GRC, Security, or FinOps .