Software Engineer - AI Platform (US)

Summary

Genios AI is a scrappy, data-driven startup revolutionizing financial workflows using AI. They are seeking a Software Engineer to build and scale AI products, focusing on integrating advanced AI workflows into production systems.

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

Skills

• 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
• Autonomous and excited about taking ownership over major initiatives
• Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle
• Production experience with LLMs (APIs or custom implementations) at meaningful scale
• Experience building agentic systems or LLM-enabled products
• Familiarity with prompt tuning methodologies and frameworks like self-prompting, DSPy, or Banks
• Experience with performance optimization and high-scale document indexing systems
• Prior startup experience, grit, and ability to thrive in fast-moving environments
• Familiarity with databases and comfortable writing SQL queries

Qualifications

Must Haves

• 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
• Autonomous and excited about taking ownership over major initiatives
• Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle

Nice to Haves

• Production experience with LLMs (APIs or custom implementations) at meaningful scale
• Experience building agentic systems or LLM-enabled products
• Familiarity with prompt tuning methodologies and frameworks like self-prompting, DSPy, or Banks
• Experience with performance optimization and high-scale document indexing systems
• Prior startup experience, grit, and ability to thrive in fast-moving environments
• Familiarity with databases and comfortable writing SQL queries

Benefits

• Competitive Compensation
• Unlimited PTO
• AI Assistants for work (Coding, General Purpose, etc.)