Senior AI Engineer

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Calliere Group

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2008

🤝 B2B

🎯 Recruiter

B2B • Recruitment • IT Recruitment

Calliere Group is a boutique organization that specializes in executive search, talent acquisition, and advisory services, primarily focused on the technology and professional services sectors. With a team composed of experts with Fortune 500 experience, they provide tailored and collaborative solutions designed to align organizational needs with top-level talent, ensuring outstanding business outcomes for their clients.

📋 Description

• Design, implement, and deploy AI/ML systems end-to-end, from prototypes to hardened production services • Build and maintain data pipelines, retrieval layers, and training/inference workflows that support LLM and other model types • Develop and evolve retrieval-augmented generation (RAG) setups, including chunking strategies, embedding selection, and vector search design • Implement and tune agentic / multi-step workflows that orchestrate tools, APIs, and models to complete complex tasks • Add observability around AI behavior: evaluations, logging, metrics, and guardrails to monitor quality, drift, and failures • Integrate models with existing application backends and APIs, and design clean interfaces for internal and external consumers • Optimize systems for performance and cost (token usage, caching strategies, routing between models, etc.) • Contribute to architecture decisions, code reviews, and technical strategy within your team

🎯 Requirements

• Over 4 years of professional software engineering experience, with at least 2 years working on AI/ML features in production environments • Strong programming skills in Python (or similar languages) and solid software engineering fundamentals • Hands-on experience building with modern LLMs and generative AI tooling (prompting, fine-tuning, RAG, or agents) • Experience with at least one major cloud platform; depth with AWS is a plus • Familiarity with AI/LLM orchestration frameworks and evaluation tools • Experience designing and integrating REST or gRPC APIs • Working knowledge of containerization and orchestration (Docker, Kubernetes) • Understanding of security and safety concerns around AI systems (prompt injection, PII handling, access control, etc.) • Comfort working in ambiguous problem spaces and making pragmatic tradeoffs under constraints