Silicon Harboursiliconharbour.dev

AI Engineer

Focus FSSt. John's, NLSoftwareonsite

Design, build, and deploy production-grade AI systems.

Job Summary

We are seeking a motivated AI Engineer (1–3 years experience) to join the AI Innovation Team at Focus FS. You will contribute to designing, building, and deploying production-grade AI systems across generative AI, machine learning, and cloud-native architectures.

This role is focused on hands-on implementation in real systems, not just experimentation. You will work closely with AI Engineers, Full Stack Developers, and Product teams to turn LLM and ML capabilities into reliable, scalable SaaS features.

Key Responsibilities

  • Design, build, and deploy AI features using Generative AI, NLP, and Retrieval-Augmented Generation (RAG).
  • Implement and maintain end-to-end ML/LLM pipelines including data ingestion, training/evaluation workflows, and deployment.
  • Build production-ready services using Python (FastAPI preferred) and integrate AI models into backend systems via APIs.
  • Work with vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector) for embedding-based retrieval systems.
  • Integrate and fine-tune LLMs via APIs (OpenAI, Azure OpenAI, Hugging Face models).
  • Develop and maintain CI/CD pipelines (GitHub Actions, Azure DevOps, or similar) with testing and version control best practices.
  • Deploy and operate AI services in cloud environments (Azure / AWS / GCP) using containers (Docker, basic Kubernetes exposure preferred).
  • Implement monitoring, logging, and evaluation pipelines for model performance and reliability.
  • Conduct A/B testing and offline evaluation to measure model quality and user impact.
  • Collaborate with cross-functional teams to translate prototypes into production-grade scalable systems.

Nice to Have

  • 1–3 years of experience in software engineering, ML engineering, or AI-focused development roles.
  • Hands-on experience building or deploying at least one production or near-production AI/ML system.
  • Strong proficiency in Python and familiarity with ML/AI frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
  • Experience working with LLM APIs (OpenAI, Azure OpenAI, Hugging Face Transformers).
  • Understanding of RAG architectures, embeddings, and vector search systems.
  • Familiarity with REST APIs, microservices architecture, and backend systems integration.
  • Basic experience with cloud platforms (Azure / AWS / GCP) and containerization (Docker).
  • Working knowledge of Git, CI/CD pipelines, and automated testing practices.
  • Experience with LangChain, LlamaIndex, CrewAI, or similar LLM orchestration frameworks.
  • Exposure to model evaluation techniques, prompt engineering, or fine-tuning workflows.
  • Understanding of MLOps practices (model versioning, deployment monitoring, rollback strategies).
  • Familiarity with event-driven architectures or streaming data pipelines.
  • Experience optimizing AI systems for latency, cost, and scalability trade-offs.

What We Value

  • Curiosity and eagerness to keep up with rapidly evolving AI technologies.
  • Practical engineering mindset balancing experimentation with production reliability.
  • Strong collaboration and communication in cross-functional teams.
  • Ability to work through ambiguity and deliver incremental, production-ready value.

What Will Help You Succeed

  • Experience deploying AI or machine learning solutions into production systems.
  • Strong proficiency in Python and modern ML frameworks.
  • Comfort working within an established AI codebase and collaborating with other AI Engineers.
  • Understanding of system performance scalability and operational considerations.
  • Ability to work through ambiguity and deliver practical AI solutions.
  • Strong collaboration and communication skills.
  • Please include examples of production AI work or projects where available.

Please include links to relevant projects or repositories where possible.

Apply Now