Manager, Technical Delivery – Engineering

AccessHope

. Own end-to-end delivery for cross-team engineering and AI initiatives, including migrations, platform rollouts, infrastructure projects, and major system changes .

Posted 11/5/2026full-timeRemote • United StatesSeniorLead💰 $100,838 - $134,622 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing end-to-end delivery of AI initiatives and software engineering projects, with a strong focus on QA processes, vendor coordination, and cross-team collaboration. Proficient in translating technical details into business-friendly language while ensuring compliance with internal standards.

Highest-signal resume keywords

AI/ML Application Development LifecycleTechnical Delivery ManagementQuality Assurance ProcessesVendor CoordinationSoftware Engineering Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringSystems DesignTechnical Delivery ManagementQuality AssuranceTest PlanningDefect ManagementArchitecture DiagramsAI/ML DevelopmentProject ManagementRisk Management

Soft Skills

Team ManagementMentoringCommunicationCollaborationProblem-Solving

Industry Keywords

Cross-Team EngineeringInfrastructure ProjectsProject DashboardsCompliance StandardsDelivery RisksTechnical DependenciesIntegration TestingLatency TrackingScalabilityTechnical Debt

About the role

Key responsibilities & impact

Own end-to-end delivery for cross-team engineering and AI initiatives, including migrations, platform rollouts, infrastructure projects, and major system changes
Maintain integrated views of milestones, dependencies, owners, risks, and decisions
Drive project plans and follow-ups across engineering, AI, product, operations, security, and other stakeholders
Identify delivery risks and blockers, including resourcing gaps, sequencing conflicts, technical debt tradeoffs, and escalate issues requiring leadership decisions
Coordinate external AI and technology partners, including deliverables, timelines, technical dependencies, open questions, integrations, testing, security reviews, and implementation
Evaluate vendor deliverables against agreed requirements and acceptance criteria
Oversee AI application development delivery across ML, backend, and platform teams
Partner with technical teams on architecture, data requirements, integrations, model evaluation, and deployment considerations
Coordinate testing and evaluation activities, including accuracy, quality, latency, and reliability tracking
Maintain documentation of technical capabilities, limitations, assumptions, and validation results
Align vendor practices with AccessHope internal policies and best practices
Own QA strategy and execution across AI products and initiatives
Define and track QA acceptance criteria for model outputs, including accuracy, reliability, bias, and edge-case handling
Coordinate QA activities across internal teams and external vendors, including test plans, defect tracking, and sign-off processes
Design test cases with AI/ML and engineering teams to validate functionality, performance, and safety before launch
Maintain QA/testing logs and ensure issues are triaged, remediated, and re-validated before go-live
Ensure AI products meet internal quality and compliance standards before production
Run delivery-focused rituals such as sprint planning, retrospectives, launch readiness reviews, and go/no-go checkpoints
Maintain decision logs, risk registers, project dashboards, and meeting outputs
Translate technical progress into clear, business-friendly language
Prepare concise delivery updates for engineering leadership
Hire and manage a team of Technical Delivery Leads
Mentor team members
May oversee a team as initiatives scale

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or similar field of study
4 years of experience plus min experience may substitute for minimum education requirements
7+ years experience in software engineering, systems design, or a technical delivery/TPM role within an engineering org
Strong familiarity with AI/ML application development lifecycles
Comfort reading architecture diagrams and discussing tradeoffs (latency, scalability, tech debt) with engineers as a peer
Experience coordinating external vendors or technology partners
Experience owning or coordinating QA processes for software or AI products, including test planning and defect management
Must be eligible to work in the U.S. without employer sponsorship for an employment visa or any other type of US work authorization
Preferred: Master’s Degree in Computer Science, Engineering, or related field
Preferred: 10+ years experience in software engineering, systems design, or a technical delivery/TPM role within an engineering org

Benefits

Comp & perks

Medical, Dental, and Vision Coverage
401(k) Plan with Employer Match
Leader Time Off (LTO)
Parental Leave
Short-Term Disability
Voluntary Benefits (e.g., life insurance, additional coverage options)
Remote work schedule
Annual incentive bonus
Support or collaboration across multiple time zones
May include travel up to 25%