AI Engineer

Genios AI
Full time
Software Development
United States
Hiring from: United States
About Us

We intend to defy the cliches while living them. Change the world working for a scrappy, data-driven, and customer-focused startup that's revolutionizing financial workflows using AI. You will be instrumental in shaping this cutting edge AI product owning features from design to launch.

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 an Applied AI Engineer who is first and foremost a strong software engineer, 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 Applied AI Engineer, 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.
  • Autonomous and excited about taking ownership over major initiatives.
  • Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle.

Bonus Points

  • 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.

Perks

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

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