Snr Full Stack Python Engineer-Agentic Systems

Job Description

Fantastic opportunity to join a world class Banking environment.

Senior Full Stack Python Engineer - Agentic Systems & Data Platforms

Seniority Level: Senior (5-8 years' experience)

Work Arrangement: Hybrid (3 days office)

Role Overview

We are looking for a Senior Full Stack Python Engineer to design, build, and deliver intelligent backend systems and modern front-end applications that support complex, data-intensive workflows.

This role sits at the intersection of distributed systems engineering, AI/agentic tooling, and front-end data visualization - ideal for an engineer who enjoys working across the full stack and translating ambiguous business problems into robust, production-grade solutions.

Key Responsibilities

• Development
• Design, develop, and maintain backend services in Python, including asynchronous task processing using Celery, Redis (as broker/result backend), Celery Beat (scheduled/periodic tasks), and Flower (task monitoring/observability).
• Build and maintain MCP (Model Context Protocol) servers and tools, exposing complex internal APIs, databases, and systems as structured, consumable tools for AI agents and applications.
• Implement and integrate LangChain and/or LangGraph based agentic workflows, including multi-step reasoning chains, tool-calling pipelines, and orchestration logic.
• Develop responsive, high-performance front-end applications using React, with a focus on complex data grids and tables using AG Grid (sorting, filtering, grouping, pivoting, server-side row models, custom cell renderers, etc.).
• Write efficient SQL queries and work with Oracle databases (schema design, query optimization, stored procedures a plus) alongside other relational/non-relational data stores as needed.
• Build clean, well-documented, and testable APIs (REST and/or MCP-based) that integrate cleanly with upstream and downstream systems.
• Contribute to architecture and design decisions, including system scalability, fault tolerance, and observability of distributed task pipelines.

Requirements Gathering & Stakeholder Engagement

• Engage directly with business users, product owners, and subject matter experts to understand workflows, pain points, and desired outcomes.
• Translate ambiguous or loosely defined business requirements into clear technical specifications and implementation plans.
• Participate in discovery sessions, demos, and iterative feedback loops to validate solutions against real user needs.
• Act as a technical liaison between engineering and business stakeholders throughout the project lifecycle.

Testing & Quality Assurance

• Write and maintain unit, integration, and end-to-end tests for both backend (Python/Celery/API) and front-end (React) code.
• Validate asynchronous task pipelines for correctness, idempotency, retry behavior, and failure handling.
• Participate in code reviews, ensuring adherence to coding standards, security practices, and performance benchmarks.
• Support UAT (User Acceptance Testing) cycles, working with end users to validate functionality before release.

Delivery

• Own features end-to-end - from requirements and design through development, testing, deployment, and post-release support.
• Work within agile/iterative delivery frameworks, participating in sprint planning, stand-ups, and retrospectives.
• Deploy and support applications in line with CI/CD best practices, ensuring smooth releases with minimal disruption.
• Monitor production systems (using tools like Flower for task queues) and troubleshoot issues across the stack.

Required Skills & Experience

• Core Language
• Strong proficiency in Python (5+ years), with deep understanding of async programming, design patterns, and performance optimization.
• Task Processing
• Hands-on experience with Celery, Redis, Celery Beat, and Flower in production environments.
• AI/Agentic Tooling
• Practical experience implementing MCP (Model Context Protocol) servers/tools
• Frontend
• Solid experience with React (hooks, state management, component architecture) and AG Grid for complex data-grid UIs
• Databases
• Working knowledge of SQL; experience with Oracle databases is a strong plus
• API Development
• Experience designing and building RESTful and/or tool-based APIs integrating with complex internal/external systems
• Testing
• Experience with automated testing frameworks (e.g., pytest, Jest/React Testing Library) and a quality-first mindset
• Collaboration
• Demonstrated ability to engage directly with business users to scope and refine requirements
• Domain Knowledge
• Familiarity with commodities markets or commodity indices is a strong plus (not mandatory)

Nice-to-Have Skills

• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with CI/CD pipelines and DevOps practices.
• Exposure to vector databases, embeddings, or RAG (Retrieval-Augmented Generation) pipelines.
• Experience with observability/monitoring stacks (Grafana, Prometheus, ELK, etc.).
• Prior experience in financial services, trading platforms, or market data systems.

What We Offer

• The opportunity to work on cutting-edge agentic AI tooling alongside robust distributed systems engineering.
• A hybrid work environment that balances in-office collaboration with flexibility.
• Exposure to real-world, high-impact business domains including commodities and market data.
• A collaborative, engineering-driven culture focused on continuous learning and delivery excellence.