AI Engineer (Backend) - Python

We are building the next generation of AI-powered applications that deliver actionable financial and marketing insights to our clients. As an AI Engineer focused on backend development, you'll be instrumental in designing and developing multiple agentic AI applications that integrate with data lakehouses and business intelligence platforms. This is not a single-project role. You'll work on a pipeline of AI-driven solutions across various use cases, all built on a common architecture leveraging cutting-edge LLM technologies, agentic frameworks, and cloud infrastructure.

What You'll Build

Agentic chatbot applications Agentic chatbot applications with conversational UI for financial and marketing insights

RAG-based systems RAG-based systems that intelligently retrieve and synthesize information from enterprise data sources

MCP (Model Context Protocol) integrations MCP (Model Context Protocol) integrations for tool calling and external system interactions

Real-time visualization generation Real-time visualization generation including graphs, charts, and dynamic dashboards

Sandboxed code execution environments Sandboxed code execution environments for safe AI-generated code runs

LLM benchmarking systems LLM benchmarking systems to evaluate and switch between models (AWS Bedrock, Azure AI Foundry) as new versions emerge

Data integration pipelines Data integration pipelines connecting to SQL-based data lakehouses and Tableau dashboards

Key Responsibilities

Development

Design and develop Python backend services using FastAPI FastAPI for AI-powered applications

Implement agentic workflows using LangChain LangChain and / or Azure AI agentic frameworks like AutoGen Azure AI agentic frameworks like AutoGen

Build and maintain RAG systems for context-aware AI responses

Develop MCP servers and integrations for tool calling and external API interactions

Create sandboxed execution environments for AI-generated code and visualizations

Data & SQL

Write efficient SQL queries against data lakehouses to retrieve business insights

Integrate with Tableau dashboards and other BI platforms

Optimize data retrieval patterns for LLM context windows

AI / ML Operations

Build benchmarking systems to evaluate LLM performance across different models and providers Implement model switching logic to automatically use the most efficient / effective LLM

Monitor and optimize token usage, costs, and response latency

Work with AWS Bedrock and Azure AI Foundry for model deployment

DevOps & Deployment

Containerize applications using Docker

Deploy and manage services in Kubernetes (K8s) clusters

Build and maintain GitLab CI / CD pipelines for automated testing and deployment

Ensure scalability, reliability, and security of production systems

Collaboration

Work directly with US-based clients to understand requirements and deliver solutions

Collaborate with frontend developers (React), data engineers, and architects

Participate in technical design discussions and architectural decisions

Document code, APIs, and system architecture clearly

Required Qualifications

Technical Skills

3+ years of professional Python development experience

Strong SQL skills with experience querying databases or data lakehouses

Experience with FastAPI or similar Python web frameworks (Flask, Django)

Hands-on experience with AWS Bedrock or Azure AI services

Familiarity with Docker containerization

Experience with Kubernetes (K8s) deployments

Proficiency with Git and GitLab CI / CD or similar CI / CD tools

Understanding of RESTful API design and development

AI / ML Experience

Working knowledge of LLM technologies (GPT, Claude, Llama, etc.)

Experience with prompt engineering and LLM application development

Familiarity with LangChain, AutoGen, Azure AI frameworks, or similar agentic / orchestration frameworks Understanding of RAG (Retrieval-Augmented Generation) patterns

Soft Skills

Excellent English communication skills (written and verbal) for US client interaction

Ability to work autonomously and complete tasks with minimal supervision

Strong problem-solving skills and attention to detail

Self-motivated with ability to manage priorities and deadlines

Preferred Qualifications

Experience with React or frontend development (bonus, not required)

Familiarity with Tableau or other BI platforms

Experience with data lakehouses (Databricks, Snowflake, etc.)

Knowledge of Model Context Protocol (MCP) or similar tool-calling frameworks

Experience building benchmarking or evaluation systems for ML models

Background in financial services or marketing analytics

Contributions to open-source AI / ML projects