Generative AI Engineer

Job Title

Generative AI Engineer

Location

Remote

Compensation

$110,000–$120,000 annually for full-time roles, or $45–$70/hour for contract engagements.

Employment Type

Full-time or Contract

Company Description

AirBills is a utility bill automation and cost optimization platform built for short-term rental (STR) and single-family rental (SFR) property owners and managers. The platform connects utility accounts from over 20,000 providers into a single dashboard, automating monitoring, payments, audits, and cost optimization. AirBills helps users avoid missed payments, reduce overcharges, and gain real-time insight into usage, savings, and alerts across properties. Serving individual homeowners through large professional and enterprise portfolios, AirBills supports owners and managers with 1 to 1,000+ doors. The company is on a mission to make utility billing smarter, simpler, and more cost-effective for rental property professionals everywhere.

Required Experience

4–7 years of experience in software engineering, AI engineering, machine learning engineering, backend engineering, data engineering, automation engineering or a similar product-focused technical role. Candidates with strong backend experience and hands-on exposure to LLM APIs, AI-powered systems or automation products may also be considered.

About the Role

We are looking for a Generative AI Engineer to build production-grade AI-powered product features, automation systems and intelligent product flows that solve real business problems. This role is suited for someone who can work with LLM APIs, prompts, retrieval patterns, embeddings and backend systems while keeping reliability, accuracy, latency and cost in mind. You will work with product and engineering teams to turn business requirements into usable AI features that can be tested, improved and deployed in real product environments.

What You’ll Work On

• Build and test generative AI product features using LLM APIs, backend services, prompts, embeddings and automation logic.
• Develop AI-powered systems that help users complete tasks, reduce manual effort or make internal processes easier to run.
• Work with retrieval, structured outputs, model evaluation, prompt design and context management to improve response quality.
• Improve accuracy, reliability, latency, cost efficiency and usability across AI-enabled product features.
• Build backend components, API connections and integration points that allow AI features to operate in production.
• Test AI outputs across different use cases, edge cases and customer environments to identify failure patterns.
• Create clear documentation for AI behavior, implementation decisions, test results and known limitations.
• Partner with product, engineering and operations teams to refine requirements, review feature behavior and improve release quality.

What We’re Looking For

• Hands-on exposure to LLM APIs, prompt-based systems, AI-assisted product features or generative AI applications.
• Understanding of retrieval patterns, embeddings, model evaluation, structured outputs or AI application design.
• Ability to build and maintain production services with attention to reliability, monitoring, latency and cost.
• Comfort working with APIs, data flows, cloud services, databases and integration-heavy product systems.
• Ability to break down business problems into clear technical tasks and practical AI product features.
• Clear written communication for documenting AI behavior, test findings, technical decisions and implementation notes.
• Ability to work remotely with product, engineering and operations teams across India, the US or other global markets.

Good to Have

• Experience with OpenAI, Anthropic, Azure AI, Amazon Bedrock, Google Vertex AI or similar AI platforms.
• Familiarity with LangChain, LlamaIndex, vector databases, RAG systems, agentic patterns, evals or AI safety controls.
• Exposure to SaaS products, B2B software, internal operations tools or enterprise product environments.
• Experience building AI features that use structured outputs, tool calling, document processing or automated decision flows.
• Familiarity with cloud deployment, observability, queues, data pipelines or model performance tracking.

Who Should Apply

You should apply if you have worked as a Generative AI Engineer, AI Engineer, ML Engineer, Software Engineer, Backend Engineer, Automation Engineer, Data Engineer, Product Engineer or in an adjacent role involving AI-powered systems, APIs, automation or production software. This role is also suitable for strong software engineers who are newer to generative AI but have hands-on exposure to LLM APIs and a clear interest in building AI-enabled products.

Equal Opportunity Statement

We know strong candidates may not match every preferred qualification. If this role fits your experience and interests, we encourage you to apply.