Company Description
Fineksi is a platform that assists financial institutions in achieving digital transformation through AI. We specialize in partnering with financial institutions to provide comprehensive, accurate, reliable, and fast AI-powered credit analysis.
Role Description
As an AI Software Engineer on our team, you will play a pivotal role in designing and building intelligent features that enhance customer value primarily using generative AI, large language models (LLMs), and agentic frameworks.
You'll collaborate closely with product and engineering leaders to ideate, prototype, and deliver AI-powered solutions that elevate the product value.
Key Responsible
- Design, develop, and deploy LLM-powered systems and AI agents.
- Develop knowledge bases by utilize vector embedding and vector db.
- Implement RAG, MCP, and advanced prompt engineering to personalize model behavior and improve model performance.
- Fine-tune pre-trained models on custom datasets to improve performance on specific tasks.
- Develop and apply frameworks to assess, validate, and refine AI model or agent performance, ensuring reliability.
- Work closely with product managers, analysts, and engineers across teams to define high-value use cases and collect requirements.
- Maintain clear documentation of models, methodologies, and testing to support organizational learning.
- Stay updated on the latest advancements in AI, LLMs, and related technologies to propose innovative solutions.
Qualifications
- Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
- 2.5+ years of professional experience in a relevant role (AI Engineer, ML Engineer, Data Scientist, or Data Engineer), with hands-on experience with NLPs, Computer Vision, LLMs and Generative AI.
- Hands-on experience working with LLMs and AI frameworks (such as OpenAI, LangChain, or Autogen).
- Expertise in Python and major ML/Data libraries such as PyTorch, TensorFlow, and Scikit-learn.
- Familiarity with AI agents and agentic orchestration patterns.
- Deep understanding of NLP fundamentals, embedding models, RAG workflows, and customization through fine-tuning.
- Proven ability to design, build, and deploy production-ready AI-powered features.
- Comfortable working in a fast-paced startup environment with evolving priorities.
- Strong problem-solving mindset and analytical capabilities, adept at bridging business needs with technical implementations.
- Ability to work independently and collaboratively in a hybrid environment