AI engineer for clinical research

Acuity Analytics; Lisboa; On-site; EUR 90,000 - 120,000; Full time

Job summary

Acuity Analytics ищет опытного инженера по ML и разработке ПО для взятия под управление архитектуры продакшна многоп-agentной системы. Вы будете отвечать за структуру оркестрации, обработку шагов и хранение метаданных в безопасном и масштабируемом окружении.

Требуется ветер в клинке коду на производственном уровне, включая CI/CD, тестирование и документирование. Работа предполагает тесное сотрудничество с экспертами-доменниками и улучшение аналитических процессов в рамках Azure и PostgreSQL.

Qualifications

• Опыт разработки ПО и ML-энергических систем.

Responsibilities

• Владеть архитектурой производства многокомпонентной системы и обосновать выборы метриками.
• Перейти от прототипа к работе в продуктивной среде, усилить детерминированное ядро и обеспечить обработку сбоев, мониторинг и учёт затрат.
• Соблюдать процесс CI/CD, код-ревью, контроль версий и управление окружениями.
• Работать с доменными специалистами — перевод правил в точные спецификации.

Job description

Описание

Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base, and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organisations. To our customers, we bring a partnership that provides the talent, technology, and capability to enhance performance and operational efficiency.

Задачи

Own the production architecture: decide how the multi-agent system is structured (orchestrator, parallel workers, independent checkers, repair loops) and defend those choices with measurements. Take systems from prototype to live: harden the deterministic backbone around the agents (step orchestration, status tracking, caching, validation gates, resumable runs), including failure handling, cost and latency control. Make quality provable: build evaluation harnesses and test layers so every change is scored against reference results before release. Operate what you ship: monitoring, per-step cost and token accounting, incident handling and release notes. Build the data layer: move run state, metadata and outputs to Postgres and Azure Data Lake Storage, with access control and audit trails. Set the standards: code review, CI/CD, branching, pre-commit and secret scanning, reproducible environments, validation documentation. Raise the bar for the engineers around you. Work with domain experts: turn the rules clinical programmers and statisticians write into precise, testable specifications.

Требования

Senior level (typically 8+ years in software or ML engineering) with a track record of multiple systems shipped to production and run in live use.

Be ready to walk us through them: what you built, what failed, what you changed.

Production Python (3.12): typed, packaged, tested code (pytest, ruff, pre-commit), clean module structure, no notebook-only work.

Agents built on Claude (Claude Agent SDK or Claude Code, tool use, prompt design, structured outputs), with experience keeping long agent sessions reliable and detecting when an agent stops early or invents output.

Multi-agent systems in production: orchestration, parallelism, dependency ordering, independent verification, failure handling, cost control.

Evidence from live systems, not only demos.

Testing and evaluating LLM systems: fake or recorded backends, deterministic tests for the surrounding code, separate evals for model output.

Git and CI/CD at team scale: pull-request workflow, GitHub Actions or Azure DevOps pipelines, Docker, versioned releases.

Cloud and data: PostgreSQL (schema design, migrations, audit tables), Azure Data Lake Storage / Blob, Parquet, pandas/pyarrow.

GxP delivery: you have built or supported software under validation: traceability from requirement to test, audit trails, change control, access control, documentation.

Будет плюсом: CDISC SDTM/ADaM knowledge, or pharma/CRO analytics experience; Ability to read SAS or R clinical programs; Domino Data Lab or similar job-based compute platforms; Azure Key Vault, managed identity, Azure DevOps Test Plans; MCP servers, long-document retrieval, prompt caching, agent observability and tracing

Условия

At Acuity Analytics, you'll have the opportunity to work across complex enterprise Azure environments while helping shape and improve our Managed Services capability.

You'll solve challenging technical problems, influence standards and automation, mentor other engineers, and work closely with customers and technical teams.

People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive.