AI Product Founding Engineer

Overview

We are seeking an AI Product Founding Engineer to help build and scale an enterprise AI platform focused on agentic systems, intelligent workflows, and AI-powered productivity solutions.

This is a highly strategic role that combines technical leadership, hands-on engineering, architecture, and product ownership. The ideal candidate will help shape platform strategy, influence architecture decisions, build critical capabilities, and partner closely with product and engineering leadership to define the future of enterprise AI.

The role is approximately 70% engineering/architecture and 30% product strategy.

Key Responsibilities

Architecture & Technical Leadership

• Define architectural direction for enterprise AI and agent platforms.
• Drive technical decision-making, architecture reviews, and design documentation.
• Evaluate build vs. buy opportunities across AI infrastructure and tooling.
• Design scalable governance, security, identity, compliance, and auditing capabilities.
• Establish engineering best practices for AI applications, including testing, evaluation, monitoring, and release management.

Platform Engineering

Build core capabilities including:

Agent Orchestration & Workflow Automation

• Design workflows that combine deterministic business logic with LLM reasoning.
• Develop multi-agent systems that remain scalable and observable.

Autonomous Agent Frameworks

• Enable agents to operate on events, triggers, schedules, and approval workflows.
• Build infrastructure for governed autonomy and human-in-the-loop controls.

Agent Identity & Lifecycle Management

• Ownership and access controls
• Agent provisioning and retirement
• Auditing and governance

Integrations & Tooling

• Connect AI systems with enterprise applications and services.
• Implement modern agent protocols, skills frameworks, and extensibility patterns.

Evaluation & Observability

• Create frameworks for measuring AI effectiveness.
• Implement monitoring, tracing, evaluation, and explainability systems.

Retrieval & Knowledge Systems

• Design secure retrieval architectures.
• Build scalable knowledge and document retrieval capabilities.
• Ensure permission-aware access to enterprise knowledge sources.

Product Ownership

• Partner with product leadership on roadmap planning and prioritization.
• Define product requirements, success metrics, and acceptance criteria.
• Lead pilot programs and iterative launches.
• Gather user feedback and translate insights into platform capabilities.
• Focus on measurable business outcomes and adoption.

Security & Governance

• Design enterprise-grade AI governance and security controls.
• Address AI-specific security risks including prompt injection, data exposure, tool misuse, and agent abuse.
• Partner closely with security and compliance teams.
• Support regulatory, audit, and compliance initiatives.
• Implement robust deployment controls, approval workflows, and operational governance.

Required Qualifications

AI & Agent Systems

• Experience building and shipping production AI applications.
• Hands-on experience with LLM-based systems beyond proof-of-concepts.
• Experience with agent frameworks and orchestration platforms.
• Deep understanding of:
• Retrieval-Augmented Generation (RAG)
• Vector search and embeddings
• Hybrid search architectures
• Re-ranking strategies
• Permission-aware retrieval
• Experience building multi-agent systems and tool-calling workflows.
• Strong understanding of evaluation methodologies for AI systems.
• Experience optimizing model performance, latency, and cost.
• Knowledge of AI security and adversarial attack mitigation.

Software Engineering

• Full-stack development experience in production environments.
• Strong skills in:
• TypeScript
• Node.js
• React
• Python
• Experience with cloud-native architectures (Azure preferred).
• Containerization and modern deployment practices.
• Experience building resilient systems around AI services.
• Knowledge of:
• Relational databases
• Vector databases
• Data ingestion pipelines
• Document processing systems

Platform & Cloud Architecture

• System architecture ownership and leadership experience.
• Strong cloud architecture background including:
• Identity & access management
• Secrets management
• Networking
• Cost optimization
• Experience with Infrastructure-as-Code solutions (Terraform, Bicep, etc.).
• CI/CD, GitOps, and automated deployment pipelines.
• Kubernetes or managed container platforms.
• Observability, monitoring, scalability, and reliability engineering experience.
• Multi-tenant architecture design experience.

Product & Leadership

• Ability to write clear technical and product specifications.
• Strong prioritization and decision-making skills.
• Experience balancing technical excellence with user adoption.
• Strong communication and stakeholder management abilities.
• Ability to thrive in ambiguous, fast-moving environments.

Preferred Qualifications

• Experience within regulated industries or enterprise environments.
• Microsoft ecosystem expertise:
• Azure
• Entra ID
• Microsoft Graph
• Microsoft 365 extensibility
• Databricks experience.
• Enterprise SaaS platform experience.
• Compliance experience (ISO 27001, ISO 42001, SOC 2, FedRAMP, etc.).
• Knowledge engineering, semantic layers, or graph-based data systems.
• Digital twins, IoT, operational technology, or sensor-based systems experience.
• Geospatial, BIM, CAD, engineering, or asset-management technology experience.
• Open-source contributions related to AI tooling or agent ecosystems.