Sr. Director, Architecture and AI

Innovation Associates, Inc. • US,

11d • $212,500 - $287,500

About The Position

iA is looking for a Sr. Director, Architecture and AI to lead enterprise-wide architectural transformation across the organization. This is a hands-on leadership role for someone who has modernized legacy monolithic systems, brings an AI-first mindset, and can translate technical strategy into practical, scalable solutions in a fast-paced growth environment. In this role, you will set architectural direction while staying close to the work — partnering with engineers, reviewing designs, shaping governance, and contributing to reference implementations and prototypes that move the organization forward. You will help decompose iA’s long-standing .NET/VB6 monolith into modern, scalable services while introducing AI-native architecture, disciplined AI governance, and production-ready AI capabilities across the company. You will also provide leadership for iA’s cloud-based Enterprise Analytics & Insights platform and serve as a key connector between software, data, AI, and hardware teams. Success in this role will be measured by the business and customer outcomes modernization enables — including improved scalability, operational efficiency, product velocity, and long-term growth.

Requirements

• 15+ years in software architecture and engineering leadership, including direct, hands-on ownership of large-scale system modernization.
• Demonstrated success leading the modernization of legacy monolithic applications, including .NET, VB6, or comparable legacy stacks, into scalable, modern services architectures.
• Deep, working knowledge of LLMs and agentic AI systems, including how they are architected, deployed, evaluated, secured, and scaled in production environments.
• Leadership of production AI agent initiatives, including agentic developer and QA tooling such as code generation, automated test generation, code review, or migration agents.
• Background owning or architecting cloud-based enterprise analytics, insights, or data platforms at company-wide scale
• Experience applying Land, Adopt, Expand, and Retention (LAER) or comparable customer-lifecycle metrics to connect data, AI, and product strategy with customer adoption, expansion, retention, and business growth.
• Proven ability to lead, develop, and align mid-sized engineering and architecture teams across multiple product or functional areas.
• Proven ability to lead across software and hardware/physical systems, including shared architecture decisions and technical trade-offs.
• Experience in a growth-equity environment where technical decisions are explicitly tied to value creation and exit outcomes.
• Track record of making complex technical and business trade-offs and communicating decisions clearly to engineering and executive audiences.
• Applicants must be authorized to work for ANY employer in the U.S. Employer will not sponsor applicants for work visas.

Nice To Haves

• Experience with platforms similar in nature to NEXiA — high-throughput operational systems with distributed processing units and service scaling demands.
• Background bridging enterprise IT and R&D, having driven transformation across an organization rather than within a single function.
• Familiarity with regulatory or compliance-heavy environments where AI safety and governance carry real operational stakes.
• Direct experience building internal developer-productivity or QA platforms and measuring their adoption and impact.

Responsibilities

• Lead the strategy and execution for modernizing the .NET/VB6 monolith into scalable, independently deployable services while balancing business continuity, technical risk, and delivery pace.
• Lead the definition of target-state architecture, service boundaries, data ownership, and integration patterns, translating architectural strategy into working reference implementations and prototypes.
• Lead strategic trade-off decisions across build vs. buy, rewrite vs. wrap, and speed vs. architectural rigor, clearly connecting recommendations to business impact.
• Set the architectural direction for AI-first service design, embedding AI capabilities into core logic, workflows, and decision points rather than treating them as downstream enhancements.
• Establish a scalable AI practice for iA, including reusable patterns, shared infrastructure, and reference architectures that accelerate consistent, enterprise-wide AI adoption.
• Serve as a member of the Core AI Governance team with responsibility for end-to-end governance of production AI systems, including model risk, data privacy, human-in-the-loop controls, evaluation, monitoring, safety guardrails, and issue response.
• Lead the architecture, development, and scaling of production-grade AI agents, bringing hands-on expertise in agent orchestration, tool use and permissioning, memory and context management, cost and latency optimization, and failure handling.
• Set technical standards for production AI agents, including orchestration, tool use and permissioning, memory and context management, cost and latency optimization, and failure handling at scale.
• Establish governance and operational practices for evaluating, monitoring, and safely rolling back agents in production, ensuring productivity gains do not compromise code quality, security, or reliability.
• Advance agentic tooling as an enterprise capability, creating reusable patterns that scale developer and QA productivity gains across teams.
• Lead AI-enabled scaling strategies for iA’s PoDs, SSP, and MDS within the NEXiA platform, improving throughput, reliability, and operational efficiency as platform usage grows.
• Ensure scaling strategies for PoDs, SSP, and MDS are informed by hardware dependencies, physical system constraints, and operational requirements across the NEXiA platform.
• Use Land, Adopt, Expand, and Retention (LAER) metrics to guide architecture and AI investment decisions, ensuring technical priorities are directly tied to measurable customer adoption, expansion, retention, and business growth.
• Land: Accelerate onboarding and initial implementation through AI-enabled workflows that shorten time-to-first-value for new customers.
• Adopt: Increase feature and workflow adoption by using AI and agentic tooling to surface next-best actions for customers and internal teams.
• Expand: Use AI-informed signals to identify upsell and cross-sell opportunities, ensuring platform architecture supports growth without significant rework.
• Retain: Apply AI-driven early warning signals to identify churn risk, reliability concerns, or performance issues before they become customer-facing problems.
• Translate architecture and AI initiatives into LAER-based business narratives for executives and PE sponsors, showing how technical investments drive customer adoption, expansion, retention, and growth.
• Provide hands-on technical leadership through production code contributions, pull request reviews, architecture spikes, and proof-of-concept development that validates architectural direction.
• Influence strategic decisions through technical credibility, data-informed recommendations, and working prototypes that demonstrate feasibility and business impact.
• Lead and unify a 6–10-person team of architects and engineers across multiple R&D teams around shared architecture and AI standards, while balancing team-specific priorities, constraints, and delivery needs.
• Build, mentor, and mature an architecture and AI engineering bench that can sustain and scale modernization, AI-first architecture, and agentic tooling capabilities across the company.
• Own the architecture and strategic roadmap for iA’s cloud-based Enterprise Analytics & Insights platform, ensuring data quality, platform scalability, and AI/agentic capabilities are aligned across the teams that build and operate it.
• Align the platform’s architecture with the broader modernization strategy to ensure consistent technical direction across the enterprise.
• Use the platform to define, validate, and scale reusable AI-first patterns, including insight generation, anomaly detection, and agentic analytics, that can be adopted across the enterprise.
• Lead architectural alignment between software, AI, and hardware teams, ensuring system designs account for hardware dependencies, integration points, and physical constraints.
• Identify and lead AI and agentic opportunities within hardware-adjacent workflows, including operational monitoring and scaling decisions for PoDs, SSP, and MDS across the NEXiA platform.
• Lead cross-functional alignment between software and hardware teams, ensuring architecture decisions reflect full-system trade-offs across software, hardware, integration, and operational constraints.

Benefits

• Generous time off policy that allows you to put your family first
• Opportunity to work on the cutting edge of pharmacy automation in a high growth tech company
• Competitive benefits, salary, and talent development opportunities
• Commitment to professional development and working for a company where your voice is heard

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed