About the Role

The future of AI doesn’t just depend on smarter models, it depends on the systems that bring them to life.
We’re building those systems.
As an AI Systems Engineer, you’ll design and deploy intelligent architectures powered by LLMs, multi-agent systems, and RAG pipelines. You’ll operate where AI research meets real-world engineering, transforming cutting-edge ideas into scalable products that automate complex business processes and deliver measurable impact.

This is a hands-on role for builders who love both innovation and execution - crafting autonomous AI workflows, integrating diverse APIs, and deploying production-grade AI systems in modern SaaS environments.

Key Responsibilities

• Architect and build end-to-end AI solutions leveraging LLMs, LangGraph, and FastAPI, enabling intelligent automation for enterprise-scale applications

• Design, build, and optimize multi-agent frameworks for coordination, tool use, and autonomous reasoning. Implement StateGraph or similar orchestration frameworks for complex, interdependent workflows
• Develop and deploy RAG systems using Azure AI Services or equivalent — handling document ingestion, vector database integration, and context-aware retrieval for personalized user experiences
• Create conversational AI agents that understand multi-turn context, perform task automation (e.g., candidate/job creation, document summarization), and enhance decision-making through natural interaction
• Integrate diverse APIs (e.g., Recall.ai, Deepgram, CRM or HR systems) for seamless, end-to-end automation across business platforms
• Monitor and improve latency, accuracy, and scalability of AI pipelines. Define evaluation metrics for agent performance, retrieval precision, and generative reliability
• Work closely with product, data, and backend teams to define AI features, assess feasibility, and align technical solutions with business goals

Candidate Requirements

• Proven experience designing, building, and shipping AI-powered features that solve real business problems
• An experimental, curious mindset with a drive to tackle open-ended challenges.
• Deep, hands-on familiarity with the modern AI stack — RAG, vector databases, prompt engineering, fine-tuning, and evaluation frameworks
• Ability to balance innovation and reliability, grounding cutting-edge research in scalable, production-ready systems

Expertise in one or both areas

• Software Engineering & Systems Design – Strong Python skills, experience building scalable APIs/services (e.g., FastAPI, Django), and solid understanding of infrastructure, CI/CD, and system design
• ML Engineering & Research – Proficiency in ML frameworks (PyTorch, TensorFlow, Hugging Face) with a strong grasp of model architecture, training, and optimization

Disclaimer:

This job posting is not open to recruitment agencies. Any candidate profile submitted by a recruitment agency will be considered as being received directly from an applicant. Contango reserves the rights to contact the candidate directly, without incurring any obligations or liabilities for payment of any fees to the recruitment agency.