Full Stack Engineer - Backend Focused

We are looking for a Full Stack Senior Software Engineer with backend proficiency to join an Agent Development Squad building AI-powered financial close automation. You will primarily own the Python backend services, APIs, and data pipelines that power AI agents for financial close automation. You are expected to have a working understanding of containerization and deploying applications in Kubernetes environments. You should also be able to make front-end fixes and contribute to Angular UIs when needed. Full stack delivery is the expectation, with backend as the primary strength.

What You'll Do

• Build and maintain scalable RESTful APIs and microservices using Python and FastAPI.
• Design and implement async task processing flows using Redis/Celery or equivalent message queue systems (RabbitMQ, SQS, or similar) for agent job execution.
• Own data layer design, covering PostgreSQL schema design, migrations, and query optimization for agent state and audit data.
• Containerize services using Docker and deploy to Kubernetes (AKS) environments.
• Integrate backend services with the agent orchestration engine under the Tech Lead's architectural direction.
• Contribute to API contract design, covering Open API specifications, versioning, and inter-service communication patterns.
• Make frontend code fixes and contribute to Angular UI features when needed, as full stack delivery is expected.
• Lead and actively contribute to low-level design, including component design, data modelling, API contracts, and service internals; expected to articulate and defend design trade-offs during sprint planning, tech reviews, and design sessions.

Who You Are

Low-Level System Design - Core Expectation

• Proven ability to design individual service components from first principles, including data models, API contracts, internal state management, and inter-service communication patterns.
• Able to reason through and clearly articulate trade-offs between design choices, such as sync vs async processing, SQL vs NoSQL storage, REST vs event-driven communication, and monolith vs microservice boundaries.
• Expected to produce and review low-level design artefacts, class diagrams, sequence diagrams, and data flow descriptions that are precise enough for engineers to implement without ambiguity.

Backend Engineering - Primary Gate

• 5+ years of backend or full stack software engineering experience.
• Strong Python proficiency with FastAPI or equivalent async REST framework for building production-grade service APIs.
• PostgreSQL at production level, covering schema design, query writing, indexing, and migrations.
• Redis and Celery or equivalent message queue system (RabbitMQ, SQS, or similar) for async task queuing and job state management.
• REST API design experience, including OpenAPI contracts, versioning, and microservice communication patterns.
• Azure DevOps CI/CD pipeline integration for build, test, and deployment; proficient with Git and agile sprint-based delivery.

Infrastructure - Required at Working Level

• Docker for containerizing Python services, including image build and optimization.
• Kubernetes for deploying, configuring, and troubleshooting containerized workloads; working knowledge of deployments, services, config maps, and resource management is sufficient. Cluster operations ownership is not required.

Frontend Contribution - Required

• Angular at working capability to make frontend code fixes, implement UI changes, and debug components. Deep proficiency is not required.
• TypeScript at working level for reading and writing Angular component code.

AI-Native Mindset

• Comfortable working in an AI-native engineering environment where sprint discussions, design reviews, and acceptance criteria routinely involve LLM and agent concepts.
• Exposure to LangChain / LangGraph or LLM integration is a plus. Willingness to ramp up quickly is the requirement.

Nice to Have

• Experience with Identity Provider (IDP) integration and OAuth 2.0 / OpenID Connect flows.
• Familiarity with API Gateway patterns, including authentication, rate limiting, and routing.

What You'll Learn & Gain

• Hands-on experience building backend services that directly power production AI agents used in enterprise financial close workflows.
• Practical exposure to LLM and agent orchestration patterns, working alongside Senior AI/ML Engineers in a cross-functional squad.
• Experience deploying and operating containerized microservices in an Azure-hosted Kubernetes environment at enterprise scale.
• A collaborative squad environment where backend quality, API design discipline, and low-level engineering rigor are valued and developed.

Interested candidates are requested to share their updated CVs at [email protected] for further consideration.