Company Description
Ranger AI transforms how teams in energy, manufacturing, contracting, and pharma manage commercial operations through an AI-powered proposal management platform.
The platform helps enterprise teams improve workflows across RFPs, RFQs, proposals, quotations, legal review, and other complex commercial processes.
Ranger is backed by Bonfire Ventures, Inovia Capital, 25Madison, and Panache Ventures.
Role Description
This is a remote/hybrid role for an Applied AI Engineer at Ranger AI.
You will work directly with enterprise customers to understand their workflows, identify where AI can create value, and build solutions that move those workflows into production. You will work closely with Product, Forward Deployed Engineering, GTM, and our customers across discovery, solution design, implementation, testing, and deployment. The role requires strong technical ability, but also strong business judgment. You need to be comfortable speaking with customers, understanding how their business works, translating business problems into technical requirements, and building AI systems that are reliable enough for real enterprise use.
What You Will Do
- Work directly with enterprise customers to understand workflows, requirements, data, and business objectives.
- Translate customer problems into practical AI solutions.
- Design and build LLM-powered workflows, agents, retrieval systems, and automation.
- Build applications using structured and unstructured enterprise data.
- Develop and improve RAG pipelines, tool use, prompting, structured outputs, and agent workflows.
- Work with APIs, databases, document pipelines, and enterprise integrations.
- Collaborate closely with Product Managers and Forward Deployed Engineers on customer deployments.
- Prototype new AI capabilities quickly and take successful prototypes into production.
- Evaluate model performance, accuracy, reliability, and failure modes.
- Improve existing AI workflows based on customer feedback and production usage.
- Help determine when a customer problem should be solved through prompting, workflow design, retrieval, software engineering, or model changes.
- Support customer testing, technical discussions, and go-live.
- Document technical decisions, system behavior, and implementation requirements clearly.
What We Are Looking For
- 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.
- Experience with Python and modern backend development.
- Experience working with APIs, databases, data pipelines, and cloud infrastructure.
- Strong understanding of prompting, retrieval, tool use, structured outputs, and model evaluation.
- Experience taking AI applications from prototype into production.
- Strong communication skills with both technical and non-technical stakeholders.
- Comfortable working directly with enterprise customers.
- Ability to understand a business process and translate it into a technical solution.
- Comfortable working in an early-stage environment with ambiguity and changing requirements.
- High level of ownership and ability to independently drive projects forward.
Business & Customer Experience
We strongly value engineers who understand the business problem behind the technology.
You should be comfortable asking customers questions about how they work, why a process exists, where the bottlenecks are, and what success looks like.
A 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 other industrial environments.
- Experience with enterprise workflows such as RFPs, RFQs, quoting, proposals, contracts, or document review.
- Previous experience in a customer-facing technical role.
- Experience with AWS, Azure, or GCP.
- Experience with Docker and production infrastructure.
- Experience with knowledge graphs, vector databases, or enterprise search.
- Experience building agentic systems with multiple tools or workflows.
- Experience at an early-stage startup.
Compensation
- $110,000–$140,000 CAD base, depending on experience
- Extended health benefits
- Opportunity to work directly with enterprise customers and help build applied AI systems used in real industrial workflows
