Generative AI Developer enhancing AI capabilities for Finout's FinOps SaaS platform. Designing, building, and deploying generative AI-powered features in a collaborative environment.
Responsibilities
Lead the charge in transforming our product and preparing it for the agentic age.
Design, build, and deploy generative AI-powered features across our product.
Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs.
Prototype and validate new AI use cases quickly and iterate based on internal and external feedback.
Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production.
Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).
Live in the future and track new innovations and paradigms in this fast evolving field and identify opportunities to integrate them into the product.
Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs.
Optimize model performance, inference time, and cost efficiency within AWS infrastructure.
Requirements
3+ years of hands-on experience in software engineering, with at least 1–2 years working on generative AI projects (LLMs, diffusion models, multimodal models, etc.)
Proven ability to go from idea to production—ideally with examples of real-world AI features you’ve shipped
Fluency in Python, Node.js, or similar languages used in ML and full-stack development
Experience with prompt engineering, fine-tuning, or embedding models using frameworks like LangChain, LlamaIndex, or similar
Familiarity with AWS services and best practices, including Lambda, S3, SageMaker, ECS/EKS, Bedrock etc.
Experience with MLOps and model deployment practices (e.g., containerization, GPU inference, vector databases)
Creativity and initiative—able to pitch and prototype ideas with minimal oversight
Strong communication skills and the ability to explain technical concepts to non-technical stakeholders.
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