Open role

Software Engineer, AI Product

Ingénieur·e logiciel, produit IA

Remote (EST timezone) • Remote • Full-time Contract • Req ID: GDBI-4N6P8K2M

Apply Back to careers

Software Engineer, AI Product

Location: Remote (EST preferred) • Type: Full-time • Status: Open
About Global Data and BI Global Data and BI is hiring on a rolling basis for Data, BI & Analytics and ML/AI projects for large corporations. Beyond consulting services, we build production-ready business platforms and SaaS applications that leverage modern cloud technologies, data analytics, and AI capabilities. We deliver enterprise-grade solutions with certified engineers in AWS and Microsoft Azure / Power BI technologies. Our focus includes transformation projects in the financial industry, custom platform development, and our proprietary Noème suite of products. Our mission is to transform the corporate data journey from complexity to strategic clarity, ensuring data is not just collected, but leveraged to drive smarter decisions, stronger businesses, and lasting impact.

Summary

We're looking for an AI Product Engineer to join the team responsible for building intelligent features into our Noème product suite and enterprise data platforms. As a key contributor in shaping our AI vision, you'll help define and build cutting-edge AI-powered capabilities that make data platforms more intelligent, intuitive, and capable. You'll leverage large language models (LLMs), embeddings, semantic search, and other AI technologies to transform how enterprise users interact with their data, generate insights, and automate workflows.

What you'll do (roles & responsibilities)

  • Prototype and experiment with new AI features for data platforms, including natural language querying, automated insights generation, intelligent data categorization, and AI-assisted analytics
  • Build production AI systems that integrate LLMs, embeddings, vector databases, and ML models into core product experiences
  • Design and implement intelligent data features such as semantic search over enterprise data, natural language to SQL translation, automated report generation, and context-aware recommendations
  • Develop AI-powered data quality and governance tools that automatically detect anomalies, suggest schema improvements, and identify data quality issues
  • Create intelligent automation workflows using LLMs to help users transform data, generate code, and build complex pipelines with natural language
  • Collaborate with ML/AI teams to productionize research models and integrate them into user-facing features
  • Build scalable AI infrastructure including prompt management, LLM orchestration, embedding pipelines, and model serving
  • Implement evaluation frameworks for AI features, including monitoring quality, latency, cost, and user satisfaction
  • Work with vector databases and semantic search systems (Pinecone, Weaviate, pgvector, Elasticsearch) to enable intelligent data discovery
  • Partner with Product and Design to craft beautiful, intuitive AI experiences that feel like magic to users
  • Stay current with AI advancements including new LLM capabilities, fine-tuning techniques, RAG patterns, and agent frameworks
  • Optimize AI feature costs and performance by implementing caching, prompt optimization, and model selection strategies
  • Build full-stack AI features from UI components to backend services to data pipelines
  • Ensure responsible AI practices including security, privacy, bias detection, and content filtering
  • Collaborate cross-functionally with Data Engineering, Backend, Frontend, and Product teams to deliver integrated AI solutions
  • Contribute to technical architecture decisions for AI features and help establish best practices
  • Mentor other engineers on AI/ML technologies and product development

What you should have (Must-Haves)

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Machine Learning, or equivalent practical experience
  • 3-5+ years of software engineering experience with 2+ years building AI/ML products
  • Hands-on experience building production AI features using LLMs (GPT-4, Claude, Gemini), embeddings, and other ML technologies
  • Deep understanding of LLM capabilities and limitations including prompting strategies, context windows, token management, and model selection
  • Experience with AI/ML frameworks and tools: LangChain, LlamaIndex, Anthropic/OpenAI APIs, Hugging Face, vector databases
  • Strong full-stack development skills: You understand how parts of a system fit together from UI to data model
  • Frontend expertise with modern web technologies (React, TypeScript, JavaScript, HTML, CSS) to build beautiful AI-powered user interfaces
  • Backend development experience with Node.js, Python, or similar languages for building AI services and APIs
  • Database knowledge including relational databases (PostgreSQL, MySQL) and understanding of data modeling
  • Experience with vector databases and semantic search (Pinecone, Weaviate, Chroma, pgvector, FAISS)
  • Understanding of RAG (Retrieval Augmented Generation) patterns and building context-aware AI systems
  • Strong problem-solving skills: You approach problems holistically, think critically about implications, and balance business impact with technical excellence
  • Empathetic communication: You communicate technical decisions clearly and collaborate effectively with cross-functional teams
  • Impact-oriented mindset: You care about business impact, prioritize accordingly, and understand the balance between craft, speed, and outcomes
  • User focus: You think critically about how AI features shape real people's workflows and understand that reach comes with responsibility
  • Ability to navigate ambiguity: You can prototype quickly, validate ideas, and productionize successful experiments

Nice-to-Haves

  • Advanced ML/AI expertise including fine-tuning, model training, MLOps, and deploying custom models
  • Experience with agent frameworks and building autonomous AI systems (LangGraph, AutoGPT patterns, function calling)
  • Knowledge of prompt engineering techniques, few-shot learning, chain-of-thought prompting, and optimization strategies
  • Experience with AI safety and responsible AI including content filtering, bias detection, and security considerations
  • Understanding of data engineering and how AI features integrate with data pipelines, ETL workflows, and data lakes
  • Experience with Azure OpenAI Service or AWS Bedrock for enterprise AI deployments
  • Knowledge of semantic layer concepts and how AI can enhance business intelligence
  • Experience with BI tools (Power BI, Tableau) and understanding of analytics workflows
  • Background in natural language processing (NLP) or information retrieval
  • Experience with streaming data and real-time AI features
  • Understanding of cost optimization for LLM applications at scale
  • Knowledge of privacy-preserving AI techniques for working with sensitive enterprise data
  • Experience building AI features for financial services or other regulated industries
  • Contributions to open source AI/ML projects or active participation in AI research community
  • Familiarity with evaluation metrics for AI systems (BLEU, ROUGE, human evaluation frameworks)
  • Experience with A/B testing AI features and measuring impact
  • Bilingual proficiency in English and French (asset for Quebec clients and bilingual AI features)
  • Interest in emerging AI technologies like multimodal models, long-context models, and AI-generated code

Work details

  • Location: Remote (EST timezone preferred for team collaboration)
  • Reporting relationship: You will report to the Engineering Manager for AI Products or Director of AI Engineering

Compensation

Competitive salary package adjusted to your local market and country of residence. Compensation is location-based and reflects regional market standards. We benchmark against leading technology companies in your country to ensure competitive, fair pay for AI/ML engineering talent with product development experience.

Our commitment to diversity, equity, and inclusion We're committed to employment equity and encourage women, Indigenous Peoples, persons with disabilities, veterans and persons of all races, ethnicities, religions, abilities, sexual orientations, and gender identities and expressions to apply. We also welcome applications from Latin America countries, as the position is remote.

What happens after you apply

Timeline: We aim to complete our process within 2-3 weeks of application.

Step 1
Apply Submit your application. If you applied before and were not successful, you are welcome to apply again.
Step 2
Initial call (1 hour) If pre-selected, we schedule an initial conversation.
Step 3
Technical interview (1h30 to 2h) If shortlisted, AI/ML discussion, system design, and coding exercises.
Step 4
Panel interview (1h30) Meet with AI/Product teams to discuss product thinking and collaboration.
Step 5
Hiring decision If selected, we send an offer and next steps, otherwise we inform you by email.
If you don't hear back from us after application or any interview stage, it means we do not pursue your application.
Privacy Notice By clicking "Submit Application", I understand and agree that Global Data and BI Inc. and its affiliates will collect and process my information in accordance with Global Data and BI's Recruiting Privacy Policy available at https://globaldataandbi.com/privacy/recruiting-privacy-policy
Apply

Submit your application

We’ll email you a verification link first. Once verified, your application enters our scoring + shortlist flow.

Used to send your verification link and updates for this application.

Used only if we need to clarify availability or interview scheduling.

Helps us understand work authorization constraints for client environments.

Helps align timezone, tax/vendor setup, and client access requirements.

Please enter your rate in your local currency, based on your country of residence.

Used for fast background context (roles, dates, industries). No automated posting.

Used to review work samples where relevant (code, dashboards, writeups).

This is required so we can score applications consistently. Please do not include sensitive identifiers (passport/SIN, full home address).

Optional supporting link. If provided, it must be accessible without logging in (e.g., “anyone with the link can view”).