AI Back end Developer

We are seeking a highly skilled AI Backend Developer with very strong quantitative and analytical skills, and expertise in credit modeling, structured finance, and real-time risk assessment. The right candidate will drive the evolution of our AI-driven credit and risk management technology and be able to thrive in a fast-paced, startup-like environment, embracing quick iterations, fast shipping, and continuous optimization based on real-world usage. This role requires strong soft skills, including clear communication with stakeholders, rapid development and iteration, hypothesis testing, and customer feedback-driven product improvements.

Our platform integrates advanced AI, quantitative analytics, and structured finance models to support real-time underwriting, predictive analytics, and scalable lending solutions. We are a fast-moving fintech company leveraging AI, agentic systems, and

autonomous workflows to build the next generation of financial automation tools for emerging markets.

Position Summary:

The AI Full Stack Developer will be responsible for architecting, developing, and deploying high-performance AI-powered financial systems that enhance credit decisioning, risk modeling, and structured finance workflows. This role requires

expertise in modern AI frameworks, quantitative modeling, backend development, and cloud-based infrastructure to ensure the scalability, security, and compliance of our financial applications. Our platform integrates AI-driven workflows, real-time financial intelligence, and multi-agent AI systems with real-life avatars and voice-to- voice interaction in any language.

You will work closely with credit, risk, and data science teams to integrate machine learning models, structured finance principles, and financial decisioning systems into our platform. This role requires a deep understanding of AI-powered risk assessment, API-first architectures, and scalable cloud-based solutions.

Key Responsibilities:

Design and implement full-stack AI-powered financial applications, focusing on structured finance, credit modeling, and risk analytics.

Develop and integrate Multi-AI Agentic systems, utilizing LangChain, LangSmith, AutoGPT, BabyAGI, MetaGPT, CrewAI, and SuperAGI for reasoning, retrieval, orchestration, and automation.

Optimize LLMs and retrieval-augmented generation (RAG) systems for enhanced credit risk assessment and decision intelligence.

Utilize Vector DBs (Pinecone, Qdrant, Weaviate, Chroma) to enhance contextual AI retrieval and structured data processing.

Develop secure, high-performance APIs using FastAPI, Flask, Django, and Node.js, integrating AI models with structured finance platforms.

Implement quantitative modeling techniques for real-time loan performance monitoring, default prediction, stress testing, and credit decisioning.

Define scalable event-driven architectures using Kafka, microservices, and cloud- native design patterns.

Ensure regulatory compliance with financial industry standards, including SOC 2, PCI DSS, and GDPR.

Deploy and manage cloud-based AI applications in AWS, Azure, or GCP, ensuring scalability, resilience, and performance.

Implement best practices in DevOps, including CI/CD pipelines, containerized deployments (Docker/Kubernetes), and automated testing.

Collaborate with cross-functional teams, including credit, risk, and capital markets, to ensure that AI-driven solutions align with business objectives.

Technical Expertise & AI Tools Required:

AI/ML frameworks: Hugging Face, TensorFlow, XGBoost, LangChain, Pinecone.

Backend Development: Python, FastAPI, Flask, Django, Node.js, event-driven architectures.

Data Engineering: SQL, NoSQL, PostgreSQL, MongoDB, vector databases, Snowflake.

Cloud & Infrastructure: AWS, Azure, GCP, Kubernetes, Docker, Kafka, RabbitMQ.

Security & Compliance: FinTech regulatory frameworks (SOC 2, PCI DSS, GDPR), authentication (Keycloak/Auth0).

API Development: GraphQL, tRPC, RESTful architectures, microservices design.

AI Orchestration & Optimization: AI agent-based automation, reinforcement learning (Ray/RLlib, Gymnasium).

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Quantitative Finance, or a related field.

Master’s or PhD strongly preferred.

5+ years of experience in AI/ML-driven software development with proven expertise in structured finance, quantitative modeling, and scalable backend systems.

5+ years of experience within fintech, credit, or risk management applications.

Strong quantitative and analytical skills, with expertise in credit modeling, structured finance, and real-time risk assessment.

Proven experience working with LLMs, AI agent orchestration, and AI-powered decisioning systems.

Ability to design and deploy scalable, cloud-based AI solutions that integrate with financial applications.

Comfortable working in a fast-paced, remote, and globally distributed environment.