SWE / AI Engineer

Boulder, Colorado

Development - Back End

Permanent

Our client, a growing FinTech company, are hiring an AI Engineer to join their team in Colorado. The successful candidate will architect, develop and scale enterprise-grade multi-agent AI systems, taking ownership of complex solutions from initial design through to production deployment to shape the future of agentic AI within the financial services industry.

Responsibilities

Design and develop production-ready multi-agent AI systems using modern agent frameworks and architectures.
Build intelligent AI workflows that integrate retrieval, reasoning, tool execution, validation and compliance controls.
Develop scalable distributed services to support reliable agent execution, monitoring and fault tolerance.
Create evaluation frameworks to assess reasoning performance, accuracy, groundedness, hallucination mitigation and financial correctness.
Implement robust memory management, context handling and agent state persistence solutions.
Collaborate with Product, Design and Engineering teams to translate business requirements into scalable AI solutions.
Optimise AI systems for performance, latency, scalability, reliability and cost efficiency.
Shape architectural decisions across model serving, vector databases, orchestration platforms, caching strategies and cloud infrastructure.

Skillset

At least 6 years’ experience in Machine Learning, including 3 years building and deploying Generative AI and LLM-powered applications in production environments.
Demonstrated experience designing, developing, and deploying multi-agent AI systems.
Deep expertise across multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine-tuning, agent memory and data synthesis techniques.
Advanced Python programming skills with strong experience using modern AI and machine learning frameworks.
Proven experience building distributed systems and deploying cloud-native applications across AWS, GCP or Azure.
Experience developing monitoring, evaluation, and reliability frameworks to ensure the performance and safety of AI systems.
Strong architectural and systems-thinking capabilities, with the ability to design scalable, multi-component AI platforms.
Experience working in high-growth, fast-paced, or early-stage startup environments is highly desirable.