Senior Engineering Manager \u2013 Delivery<\/b>
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ABOUT XENONSTACK<\/b>
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XenonStack is the fastest\-growing <\/span>Data and AI Foundry for Agentic Systems<\/b>, enabling enterprises to design, deploy, and scale AI agents that deliver measurable business outcomes.
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We build enterprise\-grade platforms across the agentic stack:
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  ElixirData \u2013 Context OS for Agentic Intelligence<\/b>
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  A unified context layer powering memory, reasoning, grounding, and decision intelligence for AI agents across complex enterprise workflows.
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  NexaStack AI \u2013 Agentic Infrastructure Automation Platform<\/b>
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  A cloud\-native platform for deploying, operating, observing, and scaling agentic workloads, inference pipelines, and AI infrastructure with security, reliability, and efficiency.
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  Akira AI \u2013 Agentic AI Platform<\/b>
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  An enterprise platform for building, orchestrating, governing, and operating AI agents that automate real\-world business processes at scale.
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  Our mission is to <\/span>accelerate the world\u2019s transition to AI + Human Intelligence<\/b> <\/span>by making agentic systems <\/span>reliable, responsible, and enterprise\-ready<\/b>.
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  THE OPPORTUNITY<\/b>
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  We are seeking a <\/span>Senior Engineering Manager \u2013 Delivery<\/b> <\/span>to own <\/span>end\-to\-end product delivery execution<\/b> <\/span>across our Agentic AI platforms.
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  This role is accountable for <\/span>predictable releases, delivery rigor, and production stability<\/b>, orchestrating execution across <\/span>Product, AI Engineering, and AI Quality & Reliability<\/b>\u2014without owning architecture, product prioritization, or quality standards.
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  If you excel at <\/span>execution leadership, delivery discipline, and cross\-functional alignment<\/b>, this role is designed for you.
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  ROLE MISSION<\/b>
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  Ensure that <\/span>what is committed gets delivered<\/b>\u2014on time, with confidence, and with minimal rework\u2014while continuously improving delivery velocity, stability, and execution maturity.
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  KEY RESPONSIBILITIES<\/b>
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  1. End\-to\-End Delivery Ownership<\/b>
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  • Own delivery execution from <\/span>commitment → release → post\-release stabilization<\/b>.
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  • Drive delivery planning, sequencing, and dependency management across teams.
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  • Ensure delivery plans are realistic, transparent, and accountable.
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    2. Release Planning & Coordination<\/b>
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    • Lead release planning, cut decisions, and timelines across multiple teams.
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    • Coordinate cross\-platform releases and resolve inter\-team dependencies.
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    • Own release calendars, communication plans, and stakeholder updates.
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      3. Delivery Predictability & Risk Management<\/b>
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      • Own delivery predictability across scope, timelines, and confidence.
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      • Identify risks early and proactively drive mitigation plans.
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      • Ensure no last\-minute surprises for leadership or customers.
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        4. Go / No\-Go Readiness<\/b>
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        • Co\-own release readiness decisions with the <\/span>Head of AI Quality & Reliability<\/b>.
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        • Ensure scope completeness, known risk visibility, rollback readiness, and monitoring plans.
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        • Provide final delivery readiness recommendations.
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          5. Cross\-Functional Alignment<\/b>
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          • Act as the delivery integrator across:
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            • Product Management<\/b> <\/span>(what & why)
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            • AI Engineering<\/b> <\/span>(how)
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            • AI Quality & Reliability<\/b> <\/span>(confidence & correctness)
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            • Resolve execution friction and unblock teams proactively.
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              6. People Leadership (Delivery Track)<\/b>
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              • Lead and mentor delivery\-focused Engineering Managers and Program Leads.
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              • Build a culture of <\/span>ownership, urgency, and execution excellence<\/b>.
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              • Drive performance management and career development for delivery roles.
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                7. Delivery Metrics & Continuous Improvement<\/b>
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                • Own and report delivery KPIs, including:
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                  • On\-time delivery
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                  • Escaped defects
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                  • Rework rate
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                  • Release stability
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                  • Cycle time and throughput
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                  • Use metrics to improve systems and processes\u2014not to assign blame.
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                    8. AI\-Driven Delivery Enablement<\/b>
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                    • Champion AI adoption across delivery workflows:
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                      • AI\-assisted planning and estimation
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                      • Automated readiness and release checks
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                      • Intelligent risk detection
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                      • Partner with <\/span>AgentOps and tooling teams<\/b> <\/span>to continuously improve delivery velocity and quality.
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                        SKILLS & QUALIFICATIONS<\/b>
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                        Must\-Have<\/b>
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                        • 10+ years of engineering experience, with <\/span>5+ years in engineering management or delivery leadership<\/b> <\/span>roles.
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                        • Proven track record of delivering <\/span>complex, multi\-team enterprise software<\/b> <\/span>predictably.
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                        • Strong experience with <\/span>Agile, Scrum, and scaled delivery frameworks<\/b>.
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                        • Excellent risk management, planning, and stakeholder communication skills.
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                        • Ability to operate calmly under pressure and bring clarity in ambiguous situations.
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                          Good\-to\-Have<\/b>
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                          • Experience delivering <\/span>AI/ML or platform products<\/b>.
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                          • Familiarity with <\/span>cloud\-native architectures and DevOps practices<\/b>.
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                          • Exposure to enterprise domains such as <\/span>BFSI, GRC, Security, or FinOps<\/b>.
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                            WHY SHOULD YOU JOIN US?<\/b>
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