SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: CAD 110,000 - 140,000 / annual
Ranger AI is an AI-powered proposal management platform serving enterprise teams in energy, manufacturing, contracting, and pharma. The platform streamlines complex commercial workflows including RFPs, RFQs, proposals, quotations, and legal review.
As an Applied AI Engineer, you will work directly with enterprise customers to understand their workflows, identify where AI creates value, and build production-ready solutions. You'll collaborate closely with Product, Forward Deployed Engineering, GTM, and customers throughout discovery, solution design, implementation, testing, and deployment.
Key responsibilities include:
- Engaging directly with enterprise customers to understand workflows, requirements, data, and business objectives
- Translating customer problems into practical AI solutions
- Designing and building LLM-powered workflows, agents, retrieval systems, and automation
- Building applications using structured and unstructured enterprise data
- Developing and improving RAG pipelines, tool use, prompting, structured outputs, and agent workflows
- Working with APIs, databases, document pipelines, and enterprise integrations
- Prototyping new AI capabilities quickly and taking successful prototypes into production
- Evaluating model performance, accuracy, reliability, and failure modes
- Improving existing AI workflows based on customer feedback and production usage
- Supporting customer testing, technical discussions, and go-live activities
- Documenting technical decisions, system behavior, and implementation requirements
The role requires strong technical ability combined with business judgment. You must be comfortable speaking with customers, understanding their business operations, translating business problems into technical requirements, and building AI systems reliable enough for real enterprise use.
Requirements:
- 4+ years of professional software engineering, applied AI, ML engineering, or similar experience
- Hands-on experience building applications using LLMs, Generative AI, RAG, agents, embeddings, or multimodal models
- Strong software engineering fundamentals
- Proficiency in Python and modern backend development
- Experience with APIs, databases, data pipelines, and cloud infrastructure
- Strong understanding of prompting, retrieval, tool use, structured outputs, and model evaluation
- Demonstrated ability taking AI applications from prototype into production
- Strong communication skills with both technical and non-technical stakeholders
- Comfort working directly with enterprise customers
- Ability to understand business processes and translate them into technical solutions
- Comfort working in early-stage environments with ambiguity and changing requirements
- High level of ownership and ability to independently drive projects forward
- Background in business, consulting, product, operations, entrepreneurship, or customer-facing technical work is highly valued
Nice to have:
- Experience in manufacturing, energy, oil and gas, engineering, pharma, supply chain, or industrial environments
- Experience with enterprise workflows such as RFPs, RFQs, quoting, proposals, contracts, or document review
- Previous customer-facing technical role experience
- AWS, Azure, or GCP experience
- Docker and production infrastructure experience
- Knowledge graphs, vector databases, or enterprise search experience
- Building agentic systems with multiple tools or workflows
- Early-stage startup experience
