Backend Engineer

Descrial
Epsom, United Kingdom
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Software as a Service Cloud Computing Code Review Continuous Integration Data as a Services Data Validation Cursor
+23 more
Linux Spring Framework Python (Programming Language) PostgreSQL Open Web Application Security Query Optimization Service Design SQL Databases SQLAlchemy Large Language Models Claude Code AI Coding Agents Backend Rate Limiting Git Fastapi Event Driven Architecture Pytest AI Platforms Integration Tests Information Technology Api Management Jenkins

Job description

As a Back-End Engineer on the UK core team, you will build the services that the product runs on: multi-tenant APIs, workflow and data services, and the integration layer between the Java/Spring core platform and Python AI services. The work is production engineering for demanding enterprise users - security, auditability, and reliability are features, not chores - shipped through disciplined CI/CD alongside the Bengaluru delivery organisation., Service design and build

Design and ship REST and async services in Python 3.11+ / FastAPI and at the boundaries of the Java/Spring core, with PostgreSQL (async SQLAlchemy) persistence

Implement multi-tenant patterns properly: isolation, tenant context, role-based access, and per-tenant configuration

Own API contracts between core services and AI services; version and evolve them without breaking consumers

Write comprehensive unit and integration tests (pytest / pytest-asyncio); hold the line on code review standards

Build for observability: OpenTelemetry traces, structured logs, metrics, and actionable alerts - including token cost, model-call latency and failure rates for the AI services you sit alongside

Build quality gates for probabilistic outputs: validation, schema enforcement and safe failure behaviour when an AI service returns something well-formed but wrong

Handle security fundamentals as routine: authN/authZ, secrets, input validation, OWASP awareness, audit trails

Cloud and delivery

Deploy and operate services on AWS (EKS/ECS patterns, RDS, S3) through Jenkins CI/CD with quality gates

Contribute to performance and cost tuning: query optimisation, caching, async throughput, and right-sizing

Support LLM-adjacent workloads: queueing, rate limiting, and cost-aware orchestration of model-calling services

Requirements

Real multi-tenant or enterprise-grade system experience: isolation, permissions, auditability

5+ years of backend engineering in production SaaS or platform environments

Strong Python (FastAPI or comparable) and solid SQL/PostgreSQL; ability to work at Java/Spring service boundaries

AWS production experience; Git, CI/CD, Linux as second nature

You build with AI coding tools daily (Cursor, Claude Code or comparable) and have a considered view of where they help and where they do not

Good to have

Event-driven architectures, queues, and workflow engines

Financial-services or regulated-industry systems

Exposure to LLM service integration patterns, Bachelor’s degree in engineering, computer science, or a related field, or equivalent experience.

Benefits & conditions

You will be working closely with the Executive Committee who have over 20 years of experience in leading a company with 400+ leading clients in the alternative investment space

Competitive compensation

Opportunity to build something impactful for established and leading companies in the financial services industry

Innovative, supportive, and collaborative work environment

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About the company

Descrial is an AI work-execution platform purpose-built for alternative investment firms and their portfolio companies and securely orchestrates proprietary data, external sources, and workflows. Descrial is an important pillar of Enterprise Intelligence Orchestration (EIO) and enables it by structuring and standardizing data while embedding domain expertise, thereby enabling faster and contextual analysis, broader coverage, and more intelligent decision-making. It is backed by TresVista’s 1,800+ employees and deep domain expertise across investment diligence, research, valuation, fund administration, accounting, and data analytics. The team is small, senior, high-ownership, and in-office, with direct access to the Executive Committee.

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