Backend Software Engineer

EPIQ SYSTEMS SINGAPORE PTE. LTD.; Singapore; On-site; SGD 150,000 - 230,000; Full time

Job summary

Epiq AI Labs is building the backend services behind our AI-driven legal platform in Singapore. You will own asynchronous processing, data pipelines, the data access layer, and authentication/authorization, operating load-bearing services end to end as the platform scales.

We emphasize scalability, reliability, and production-grade instrumentation, with a modern stack and design decisions made with senior engineers. You will influence architecture and drive engineering standards across teams.

Qualifications

• 7+ years of professional experience building and operating backend services in production.
• Strong professional experience in Python development for backend services and APIs.
• Strong professional experience in C#/.NET application development.
• Strong database expertise in SQL with experience in design, queries, and performance tuning.
• Experience with at least one major cloud platform (AWS, GCP, or Azure).
• Experience with relational databases including schema design and migrations (PostgreSQL preferred).
• Experience with asynchronous processing and message queues (RabbitMQ, Kafka, etc.).
• Experience designing scalable REST APIs and service architectures used by multiple teams.
• Familiarity with containerized deployment (Docker, Kubernetes).
• Familiarity with observability practices (metrics, logs, tracing).
• Demonstrated proficiency using AI tools in software development.
• Strong written and verbal communication skills and independent problem solving.

Responsibilities

• Design, implement, test, and operate backend services and APIs that support our AI platform.
• Build and maintain asynchronous processing using message queues and dead-letter handling.
• Lead technical design discussions and author design documents.
• Implement authentication and authorization using OAuth2, OIDC, and SAML for multi-tenant environments.
• Design and optimize PostgreSQL schemas, including live migrations.
• Integrate search and vector stores like Solr and Qdrant.
• Instrument services with metrics, logs, and traces; participate in on-call rotation.
• Write automated tests and participate in CI pipelines.
• Collaborate with AI engineers, backend engineers, product, and security.

Skills

Python

C#/.NET

SQL/PostgreSQL

Cloud platforms

Asynchronous processing

REST API design

OAuth2/OIDC/SAML

Docker

Kubernetes

Observability

AI tools in development

Tools

Docker

Kubernetes

Terraform

PostgreSQL

Solr

Qdrant

RabbitMQ

Kafka

Prometheus

Grafana

Job description

Epiq AI Labs is the innovation and engineering hub behind Epiq's next‑generation AI platform for corporate legal departments and global law firms. We operate as a startup within a global organization, focused on agentic AI systems, knowledge-driven reasoning, and enterprise‑scale simulations. We are:

• Fast, experimental, and product-obsessed
• Highly collaborative, low-bureaucracy, deeply technical
• Backed by the resources, data access, and distribution scale of a global ALSP

We are building foundational AI systems intelligent agents, reasoning engines, knowledge bases, and structured workflows that transform how litigation, investigations, compliance, and corporate knowledge work get done.

Our culture is that of a startup: high autonomy, high trust, rapid iteration, and a team that genuinely enjoys working together.

About the Role

You will build and operate the services behind our AI-driven legal platform: asynchronous processing, data pipelines, the data access layer, and authentication and authorization. These are load‑bearing systems, owned end to end rather than in slices and as the platform grows, the surface you own grows with it.

Scalability and reliability are requirements, not later additions. Services should absorb growth in tenants, data volume, and concurrency without redesign, tolerate partial failure through retry, idempotency, and graceful degradation, and carry enough instrumentation to diagnose production behavior. We build on a modern stack and treat design as real work: choices about data models, service boundaries, and processing patterns are reasoned through and documented, made alongside senior engineers rather than inherited from them. The platform is early enough that what you build now will still be in its foundation years from now.

Key Responsibilities

• Design, implement, test, and operate backend services and APIs that support our agentic AI platform.
• Build and maintain message‑queue-based asynchronous processing, including retry and idempotency handling, dead‑letter processing, and failure recovery.
• Lead technical design discussions, author design documents, and drive design reviews across teams.
• Implement authentication and authorization functionality using OAuth2, OIDC, and SAML within established patterns, including role‑based access control for multi‑tenant environments.
• Design and optimize PostgreSQL schemas and queries, and carry out schema migrations against live production traffic.
• Integrate search and vector storage technologies such as Solr and Qdrant.
• Instrument services with metrics, logs, and traces; monitor service health and participate in the on‑call rotation.
• Write automated tests, participate in code review, and maintain continuous integration pipelines.
• Contribute to technical design documents and participate in design review.
• Collaborate with AI engineers, other backend engineers, product management, and security stakeholders.

Required Qualifications

• 7+ years of professional experience building and operating backend services in production, including leading the design and delivery of large‑scale distributed systems.
• Strong professional experience in Python development for backend services and APIs.
• Strong professional experience in C#/.NET application development.
• Strong database expertise in SQL with experience in database design, query optimization, stored procedures, and performance tuning.
• Experience with at least one major cloud platform (AWS, GCP or Azure).
• Working experience with relational databases, including schema design, query optimization, and migrations (PostgreSQL preferred).
• Experience with asynchronous or event‑driven processing, such as message queues (RabbitMQ, Kafka, or comparable) or task workers.
• Extensive experience designing and implementing scalable REST APIs and service architectures consumed by multiple teams and enterprise application.
• Familiarity with containerized deployment (Docker, and exposure to Kubernetes).
• Familiarity with observability practices, including metrics, logging, and tracing.
• Demonstrated proficiency using AI tools in software development.
• Strong written and verbal communication skills, with the ability to independently drive solutions for ambiguous technical challenges and influence engineering decisions.

Preferred Qualifications

• Experience leading technical initiatives and mentoring engineers in a fast‑paced product environment.
• Proven experience driving architectural decisions and establishing engineering best practice.
• Experience with high‑volume data or document processing pipelines.
• Experience with infrastructure‑as‑code tools such as Terraform.
• Experience with multi‑tenant SaaS architectures.
• Exposure to AI/ML systems or data‑intensive applications.
• Experience in legal technology or another regulated industry.
• Experience with authentication and authorization standards (OAuth2, OIDC, SAML).

Stack: Python PostgreSQL RabbitMQ Solr Qdrant OAuth2 / OIDC / SAML Azure Kubernetes Docker Terraform Prometheus Grafana OpenTelemetry