VP, Implementation Engineer (Remote - EST Hours)

McNeil & Co.; Raleigh (NC); Remote; USD 180,000 - 270,000; Full time

Benefits offered by this job

Medical plans

Dental and vision coverage

401k with matching

PTO 20 days

Paid holidays

Life and AD&D Insurance

Disability insurance

Parental Leave

Student Loan Assistance

Tuition Reimbursement

Backup Child and Elder Care

Job summary

Arch is seeking a VP Implementation Engineering within Strategic Analytics to own the engineering vision, strategy, and production backbone for agentic and ML systems. You will lead an organization spanning managers and senior engineers, driving scalable AI/ML delivery and a culture of rigorous, maintainable engineering practices.

The role emphasizes architecture governance, SDLC ownership, and cross-team influence to align AI initiatives with business outcomes, while enabling safe, observable,

Qualifications

• 10+ years of software engineering and/or automation engineering experience.
• 8+ years of people leadership experience, including leading other managers and leaders
• Demonstrated experience building production grade AI and/or ML systems

Responsibilities

• Translate AI strategy into scalable engineering execution—ensuring AI systems are safe, observable, cost-effective, compliant, and aligned with product and business outcomes.
• Architect and govern AI/ML system designs including multi-agent flows, complex orchestrations, RAG, classical ML services and hybrid architectures.
• Productionize AI/ML solutions into stable, low-latency, compliant, scalable applications.
• Build, lead, and develop a multi-team AI/ML engineering organization—including managers and senior engineers—setting technical standards and a culture of rigorous, maintainable delivery.
• Drive organization-wide alignment by influencing senior executives, peer engineering leaders, and product leaders; resolve prioritization conflicts and clarify accountability boundaries.
• AI/ML Lifecycle Ownership: Spearhead the AI/ML Software Development Life Cycle (SDLC) balancing rapid experimentation with scalable, production-grade engineering standards.
• Establish robust practices for versioning, deployment, CI/CD pipelines, logging, and automated rollback strategies.
• Build and operate observability, monitoring, and alerting systems to track model drift, latency, throughput, and cloud computing cost governance.

Skills

Software engineering

People leadership

Production AI/ML systems

Problem solving

Communication

Education

College degree in CS/SE/Data Analytics

Tools

Azure/AWS cloud platforms

Job description

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility.

Job Description Summary Strategic Analytics is a dynamic and growing team at Arch that drives innovation and transforms how the business operates. We build AI/ML-first products that change how Arch underwrites, services, and learn from its book — combining frontier LLMs, multi-agent orchestrations and traditional ML. Our mission is broad: agentic automation, decision support, AI/ML-driven insights, and the engineering required to make all of it production-grade. We have a strong track record of success. We aim to continue scaling these efforts and are seeking a VP Implementation Engineering to own the engineering vision, strategy, and production backbone for agentic and ML systems across Strategic Analytics. This role leads the implementation engineering (IE) function and owns the engineering practices, tooling, architectures and delivery pipelines that turn AI/ML models into reliable, scalable products — partnering closely with data scientists, data engineers, automation engineers, data visualization engineers, and platform teams. This role may sit remotely; being located near an Arch office is preferred but not required.

Key Responsibilities

• Translates AI strategy into scalable engineering execution—ensuring AI systems are safe, observable, cost-effective, compliant, and aligned with product and business outcomes.
• Architect and govern AI/ML system designs including multi-agent flows, complex orchestrations, RAG, classical ML services and hybrid architectures.
• Productionize AI/ML solutions into stable, low-latency, compliant, scalable applications.
• Build, lead, and develop a multi-team AI/ML engineering organization—including managers and senior engineers—setting technical standards and a culture of rigorous, maintainable delivery.
• Drive organization-wide alignment by influencing senior executives, peer engineering leaders, and product leaders; resolve prioritization conflicts and clarify accountability boundaries.
• AI/ML Lifecycle Ownership: Spearhead the AI/ML Software Development Life Cycle (SDLC) balancing rapid experimentation with scalable, production-grade engineering standards.
• Establish robust practices for versioning, deployment, CI/CD pipelines, logging, and automated rollback strategies.
• Build and operate observability, monitoring, and alerting systems to track model drift, latency, throughput, and cloud computing cost governance.

Required Skills / Experience

• 10+ years of software engineering and/or automation engineering experience.
• 8+ years of people leadership experience, including leading other managers and leaders
• Demonstrated experience building production grade AI and/or ML systems
• Resilient problem solving — comfortable with ambiguous problems.
• Exceptional communication and influence; able to operate across teams.

Desired Skills / Experience

• P&C insurance domain familiarity — underwriting, claims, or submission lifecycle.
• Experience with complex orchestrations and microservice designs.
• Cloud experience in Azure (preferred for our stack) and/or AWS; familiarity with private endpoints and enterprise-grade safeguards.
• Experience leading multidisciplinary teams (onshore + offshore) for technology delivery.

Education

• College degree in Computer Science, Software Engineering, Data Analytics, or equivalent practical experience.

For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

Zone 1: $180,000 - $210,000/year

Zone 2: $180,000 - $240,000/year

Zone 3: $200,000 - $270,000/year

Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

• multiple medical plans plus dental, vision and prescription drug coverage
• a competitive 401k with generous matching
• PTO beginning at 20 days per year
• up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer
• basic Life and AD&D Insurance as well as Short and Long-Term Disability
• Paid Parental Leave of up to 10 weeks
• Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care
• and more.