What are the responsibilities and job description for the Forward Deployed AI Architect position at IntePros?
Enterprise AI Systems & Applied AI DeliveryAbout the Role
We are looking for a highly technical, hands-on AI Architect to design and deploy enterprise-grade AI systems inside some of the world’s most complex operating environments.
This role is ideal for someone who combines deep software engineering experience with practical AI systems expertise and strong architectural judgment. You will work directly with customer engineering leaders, security teams, and operators to design intelligent systems that are scalable, secure, observable, and production-ready.
You will not operate as a high-level advisor removed from implementation. This role requires hands-on ownership throughout the lifecycle — from architecture and integration through deployment, optimization, and operational support.
The ideal candidate thrives in ambiguity, can reason through complex tradeoffs, and earns trust through execution and technical depth.
What You’ll DoArchitect and Deploy Enterprise AI Systems
This role follows a hybrid collaboration model with regular in-office presence (3 days per week). Candidates should be comfortable working closely with both internal teams and customer stakeholders.
Travel requirements vary based on customer engagements but expect 20-50% travel based on project and customer needs.
We are looking for a highly technical, hands-on AI Architect to design and deploy enterprise-grade AI systems inside some of the world’s most complex operating environments.
This role is ideal for someone who combines deep software engineering experience with practical AI systems expertise and strong architectural judgment. You will work directly with customer engineering leaders, security teams, and operators to design intelligent systems that are scalable, secure, observable, and production-ready.
You will not operate as a high-level advisor removed from implementation. This role requires hands-on ownership throughout the lifecycle — from architecture and integration through deployment, optimization, and operational support.
The ideal candidate thrives in ambiguity, can reason through complex tradeoffs, and earns trust through execution and technical depth.
What You’ll DoArchitect and Deploy Enterprise AI Systems
- Design end-to-end AI system architectures across models, agents, orchestration frameworks, APIs, data platforms, and enterprise infrastructure
- Define how AI systems integrate into existing enterprise environments while balancing performance, security, scalability, and operational reliability
- Establish reusable architectural patterns that enable consistency and long-term maintainability across deployments
- Build reference implementations and critical integration paths
- Review, improve, and evolve production systems over time
- Step directly into high-risk or technically complex situations to unblock delivery and drive outcomes
- Identify operational failure modes, integration bottlenecks, and security risks
- Implement guardrails for data access, identity management, auditability, compliance, and observability
- Ensure systems remain composable, adaptable, and safe as customer requirements evolve
- Engage directly with customer engineering leadership, architects, security teams, and operators
- Lead architecture sessions, whiteboard system designs, and pressure-test technical assumptions
- Translate business objectives into scalable, executable technical solutions
- Help customers operationalize AI safely within real enterprise workflows
- Improve system performance, reliability, and operational efficiency over time
- Contribute to architectural standards, tooling, and best practices across deployments
- 5 years of software engineering experience
- Proven experience designing and operating distributed systems in production environments
- Strong understanding of AI system architecture, including:
- LLMs and model serving
- Agent frameworks
- Retrieval systems (RAG)
- Evaluation pipelines
- Orchestration and workflow management
- API integrations and enterprise data systems
- Deep architectural judgment and ability to make high-impact technical decisions
- Strong coding ability with experience building production systems
- Understanding of reliability, latency, scalability, observability, and debugging in enterprise environments
- Security-first mindset with experience around:
- Identity and access management
- Data governance
- Compliance and auditability
- Secure enterprise integrations
- Strong communication and technical storytelling skills
- Ability to engage credibly with senior engineering and operational stakeholders
- Comfortable leading technical discussions and influencing through expertise and execution
- Ability to navigate ambiguity and drive alignment across teams
- Ability to travel approximately 25–50%
- Comfortable working in fast-moving customer environments
- Experience deploying AI systems in regulated or enterprise-scale environments
- Background working with cloud infrastructure and modern AI tooling ecosystems
- Familiarity with orchestration frameworks, vector databases, observability tooling, and agentic systems
- Experience balancing rapid delivery with enterprise governance and operational rigor
- Competitive compensation package with meaningful equity participation
- Comprehensive medical, dental, and vision coverage for employees and dependents
- 401(k) and additional employee benefits
- Access to state-of-the-art AI models and tooling
- Opportunity to work on high-impact enterprise AI initiatives
- Fast-moving, mission-driven culture focused on curiosity, ownership, and technical excellence
This role follows a hybrid collaboration model with regular in-office presence (3 days per week). Candidates should be comfortable working closely with both internal teams and customer stakeholders.
Travel requirements vary based on customer engagements but expect 20-50% travel based on project and customer needs.
Salary : $125 - $150