Job Description
<p>About the Role : <br/><br/>We are looking for a highly skilled and self-driven AI/LLM Engineer with a strong background in Artificial Intelligence and Machine Learning, specifically with hands-on experience in building LLM-based solutions from the ground up.
This is a unique opportunity to lead the development of AI systems that power intelligent automation and personalization across our fintech platform hosted on AWS.<br/><br/>You will work on the full lifecycle of AI product development - from problem discovery, model selection, data preparation, fine-tuning, evaluation, and deployment.<br/><br/>Key Responsibilities : <br/><br/>- Design and develop AI/LLM-based solutions from scratch for fintech use cases such as underwriting, fraud detection, intelligent chatbots, document processing, etc.<br/><br/>- Fine-tune large language models (LLMs) for custom domain-specific tasks<br/><br/>- Develop RAG (retrieval-augmented generation) systems using embeddings and vector databases<br/><br/>- Build APIs to integrate AI/LLM capabilities into production-grade fintech applications<br/><br/>- Optimize and deploy models in AWS cloud environments using services like SageMaker, Lambda, ECS, ECR, etc.<br/><br/>- Implement prompt engineering techniques to improve LLM output quality<br/><br/>- Monitor model performance and continuously improve model accuracy, latency, and robustness<br/><br/>- Collaborate closely with product, data, and engineering teams to deliver business-impacting AI features<br/><br/>Required Qualifications : <br/><br/>- Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or related fields<br/><br/>- Minimum 3+ years of experience in AI/ML, with proven hands-on experience building LLM-based solutions<br/><br/>- Strong programming skills in Python and ML frameworks like PyTorch, TensorFlow<br/><br/>- Experience with LLM platforms (OpenAI, Anthropic, Cohere, Hugging Face) and frameworks (LangChain, LlamaIndex)<br/><br/>- Expertise in prompt engineering, model tuning, tokenization, embeddings, and language model fine-tuning<br/><br/>- Good understanding of vector databases (e.g., FAISS, Pinecone, Weaviate)<br/><br/>- Strong experience in AWS cloud services, especially SageMaker, Lambda, S3, ECS, ECR, API Gateway<br/><br/>- Ability to independently take a project from ideation to deployment<br/><br/>Preferred Skills : <br/><br/>- Experience with Docker, CI/CD, serverless architecture, and observability tools<br/><br/>- Prior experience in fintech domain or regulated environments<br/><br/>- Knowledge of data privacy, AI governance, and model explainability<br/><br/>- Familiarity with OCR, NLP pipelines, and generative AI use cases<br/><br/>- Contributions to open-source AI projects or published research is a plus<br/><br/>What We Offer : <br/><br/>- Work on real-world AI problems in one of the fastest-growing fintech ecosystems<br/><br/>- Opportunity to lead and scale AI from scratch within a product-first organization<br/><br/>- Competitive salary and performance-based rewards<br/><br/>- Access to cutting-edge tools, compute resources, and global AI communities<br/><br/>- A collaborative, innovation-driven culture that values autonomy and growth</p> (ref:hirist.tech)