Change the world working for a scrappy, data-driven, and customer-focused startup that's revolutionizing financial operations with AI-driven workflow automation. We’re looking for software engineers with solid foundations in building production systems and a strong applied AI focus. You will be responsible for building functionalities into the product directly and writing production-grade code that brings advanced AI workflows into real-world use.
As an engineer at Genios, you’ll focus on making minimum loveable products powered by AI—building scalable, reliable, and user-friendly systems. You’ll work across model pipelines, infrastructure, and product layers, but with a clear emphasis on applied AI delivered in production. This role requires ownership, hands-on coding, and the ability to move fast while balancing robustness and innovation.
We have full-time roles available with remote work flexibility, hybrid, or on-site based on your preferences and seniority.
Note: This remote position requires monthly travel to the Bay area or Seattle for in person team meetings.
Key Responsibilities
- Build and scale AI/ML and GenAI pipelines from experimental workflows to production-ready systems.
- Integrate model training, evaluation, deployment, and monitoring into product workflows
- Deploy and manage GenAI solutions such as chatbots, RAG applications, and predictive analytics tools.
- Operationalize LLMs and AI agents, including prompt orchestration, chaining, and fine-tuning.
- Benchmark models, develop evaluation frameworks, and improve reliability and auditability.
- Implement observability, monitoring, and rollback mechanisms to ensure secure, scalable deployments.
- Work across the stack—from backend systems to product SDKs—to deliver AI features directly into user-facing applications.
- Prototype rapidly, gather feedback, and iterate while keeping scale and maintainability in mind.
- Own critical product components and take responsibility for delivering robust, production-grade features.
- Collaborate cross-functionally with data scientists, product managers, and engineers to scope specifications and solve real customer problems.
- Debug complex issues and perform root cause analysis across model pipelines, infrastructure, and product layers to ensure reliability and continuous improvement.
Qualifications
- BS or MS in Computer Science, Statistics, or Mathematics, or equivalent experience.
- Strong software engineering background with proven experience shipping production systems.
- 3+ years of experience in ML/DL pipelines, deployment, and applied AI solutions.
- Proficiency in Python or Go with frameworks like TensorFlow, PyTorch, Scikit-Learn, FastAPI, or gRPC.
- Experience with LLM and AI frameworks such as Langchain, LlamaIndex, Hugging Face Transformers, and OpenAI API.
- Knowledge of RAG architectures, embeddings, reranking models, and LLM-based dialogue systems.
- Experience building and scaling backend platforms, APIs, and microservices.
- Comfortable working full-stack, from model APIs down to user-facing integrations.
- Have shipped AI features that users actually use; production experience over theoretical knowledge.
- Track record of building reliable products with strong attention to detail and usability.