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)

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.

You will play a hands-on role in building and scaling asynchronous task pipelines, implementing MCP (Model Context Protocol) servers and tools around complex APIs and internal systems, and integrating LLM-based orchestration frameworks. On the front end, you'll build rich, data-dense interfaces using React and AG Grid. You will also work directly with business users and stakeholders to scope requirements, which means strong communication skills are just as important as technical depth.

Exposure to commodities markets or commodity indices is a strong plus, as this role may support tooling and data platforms used by commodities trading, research, or risk functions.

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

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.