Sr AI Engineer

About the Company

Product Squads was founded with a bold mission: to engineer capital efficiency through autonomous AI agents, exceptional engineering, and real-time decision intelligence. We’re building an AI-native platform that redefines how software teams deliver value—whether through code written by humans, agents, or both. Our stack combines agentic AI systems, ML pipelines, and high-performance engineering workflows. This is your chance to build not just models, but systems that think, decide, and act.

We’re developing AI fabric tools, domain-intelligent agents, and real-time decision systems to power the next generation of product delivery.

About the Role

The Senior AI Engineer is a highly experienced individual contributor responsible for solving complex, high-impact problems using AI in production software systems. This role focuses on building and operating applied, production-grade AI solutions, including agentic systems and AI-driven workflows that deliver measurable business value. Senior AI Engineers lead initiatives end-to-end, make critical technical decisions, and ensure AI systems meet enterprise standards for reliability, performance, safety, and cost efficiency.

This role emphasizes practical AI implementation rather than research or theoretical ML work.

Responsibilities

- AI Engineering & System Design
- Design and operate AI-enabled systems addressing complex product and business challenges.
- Build and deploy agentic systems capable of autonomous decision-making and multi-step execution.
- Define and apply patterns for managing tools, context, memory, and system boundaries.
- Select and optimize models balancing performance, cost, latency, and reliability.
- Ensure model behaviour and agent flows are testable, observable, and maintainable.

- Technical Leadership
- Lead high-impact AI initiatives from design through delivery.
- Break down ambiguous problems into clear technical solutions.
- Identify risks and implement safeguards early.
- Influence technical direction through expertise and ownership.

- AI Development Practices
- Establish best practices for:
- AI-assisted development
- Agent-based workflows
- AI-driven testing and debugging
- Prompt and context design
- Evaluation and regression monitoring
- Ensure AI becomes part of standard engineering workflows.

- Mentorship & Collaboration
- Mentor engineers through reviews and technical guidance.
- Raise AI and engineering standards across teams.
- Collaborate with product and engineering teams to deliver AI-powered features.

- Quality & Reliability
- Ensure AI systems meet enterprise security, reliability, and performance standards.
- Implement monitoring and safeguards for hallucinations, drift, and behavioral issues.
- Maintain long-term system health and operational efficiency.

- Continuous Improvement
- Stay updated on AI tools, models, and practices.
- Evaluate and responsibly adopt new AI capabilities.
- Improve AI system design and operations continuously.

Qualifications

- Bachelor’s degree in computer science, Engineering, or equivalent experience.
- Extensive experience building production software systems.
- Hands-on experience developing and operating agentic AI systems.
- Strong knowledge of model context management or equivalent approaches.
- Deep understanding of AI models, prompt design, and model trade-offs.
- Experience deploying scalable AI systems with cost and latency optimization.
- Proven ability to move AI systems from prototype to production.