Required Skills

Product & System Architect, AI/LLM Integration (Agents, RAG, AI Workflows), Specification Writing & Technical Documentation, Evaluation Frameworks & Quality Engineering, DevOps / DevSecOps / MLOps, Trust Boundary Design & AI Security

Job Description

Product Application Architect

About the Role

We are a fast-growing startup that builds AI-native products and ships them rapidly. We are looking for a Product Application Architect who can define the technical vision of our platform, translate product strategy into scalable system architecture, and elevate engineering standards through hands-on mentorship. This is a highly execution-driven role where you will actively design systems, write precise specifications, review production code, and guide engineers in an AI-augmented development environment.

Key Roles & Responsibilities

1. Technical Architecture Ownership

1. Define and own the overall product architecture, including system design, APIs, data models, and service boundaries
2. Design scalable, reliable, and maintainable distributed systems
3. Lead architecture decisions, including build vs buy, tool selection, and platform strategy

2. AI & LLM Integration Architecture

1. Design and implement AI-powered system architecture using LLMs, agents, and automation frameworks
2. Establish trust boundaries, guardrails, and context architecture for AI-driven features
3. Ensure efficient integration of RAG pipelines, memory systems, and agent workflows

3. Specification & Design Excellence

1. Write clear, detailed, and execution-ready technical specifications for engineers and AI agents
2. Define success criteria, constraints, and edge cases before development begins
3. Standardize specification practices across the engineering team

4. Evaluation & Quality Frameworks

1. Build evaluation frameworks to validate AI-powered features in production
2. Design monitoring, alerting, and failure detection systems
3. Ensure robustness by identifying and mitigating silent failures and system breakdowns

5. Problem Decomposition & Execution Strategy

1. Break down complex product features into structured, executable tasks
2. Define clear delegation models between human engineers and AI agents
3. Establish efficient workflows for AI-augmented development

6. Technical Mentorship & Team Development

1. Mentor junior and mid-level engineers through code reviews, pairing, and structured guidance
2. Improve team capability in specification writing, evaluation, and system thinking
3. Foster a culture of high-quality engineering and continuous improvement

7. Cross-Functional Collaboration

1. Work closely with Product, Design, and Leadership teams to translate product vision into technical execution
2. Align technical decisions with business goals, timelines, and cost constraints
3. Communicate architectural decisions and trade-offs effectively

8. Architecture Governance & Decision Making

1. Own Architecture Decision Records (ADRs) and maintain technical documentation
2. Prioritize and manage technical debt strategically
3. Evaluate and optimize AI cost models, token usage, and system efficiency

9. Risk Management & System Reliability

1. Identify failure patterns such as context degradation, drift, and cascading failures
2. Design resilient systems with strong error handling and recovery mechanisms
3. Implement security best practices and trust boundary enforcement

Requirements

1. 7+ years of experience in software engineering, with at least 1 year in a technical architecture, staff, or principal engineering role
2. Proven experience designing and delivering scalable production systems (distributed systems, APIs, data pipelines)
3. Hands-on experience integrating AI/LLM capabilities into production environments (beyond prototypes)
4. Strong expertise in system design, architecture patterns, and scalable application development
5. Demonstrated experience in writing clear, detailed technical specifications for engineering teams
6. Experience building evaluation, monitoring, and failure detection systems
7. Strong understanding of AI systems, including LLMs, RAG pipelines, and agent-based architectures
8. Ability to design secure and reliable systems with proper trust boundaries and guardrails
9. Experience mentoring and developing junior engineers with measurable outcomes
10. Strong problem-solving skills with the ability to break down complex systems into manageable components
11. Excellent communication skills (written and verbal) with the ability to explain complex technical concepts
12. Experience working in fast-paced, evolving environments with changing requirements
13. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern DevOps practices
14. Strong understanding of software development lifecycle (SDLC) and engineering best practices
15. Ability to balance technical decisions with business goals, cost, and scalability considerations

Equal Opportunity Statement

We value diversity and inclusion. As an equal opportunity employer, we welcome applicants from all backgrounds and walks of life.

Security & Confidentiality Statement

This role may involve access to sensitive business information. The selected candidate is expected to follow internal information security policies and maintain strict confidentiality when handling proprietary or confidential data.