Senior AI Backend Engineer - Siemens Mobility

Talent Booster; Lisboa; Hybrid; EUR 90,000 - 120,000; Full time

Job summary

Siemens Mobility is seeking a Senior Backend Engineer in Lisbon to build production-grade AI solutions and scalable AI-enabled services. You will design, implement, and deploy systems centered on LLMs, RAG, and vector search, collaborating with cross-functional teams to turn AI prototypes into robust software.

The role emphasizes experience bridging data science workflows with reliable software engineering and requires hands-on work with MLOps practices in a hybrid Lisbon environment.

Qualifications

• At least 5+ years of Backend Development experience.
• Strong Python (3.11+) with async/await, typing, and Pydantic.
• Bridge experimental Data Science workflows with reliable software engineering practices.
• Experience with Docker, CI/CD, testing frameworks (pytest), code quality tools (ruff, mypy), Git workflows and reviews.
• Exposure to AI, NLP, or Information Retrieval.
• Hands-on with LLMs, Prompt Engineering, RAG, GraphRAG, Vector databases/OpenSearch.

Responsibilities

• Collaborate with engineering, operations, and stakeholders to design AI-driven solutions.
• Translate requirements into scalable AI-enabled services and technical concepts.
• Contribute to the design and architecture of AI-powered systems using LLMs and retrieval tech.
• Build production-grade AI services focusing on LLMs, RAG pipelines, and vector search.
• Own the full development lifecycle: architecture, implementation, testing, deployment, and monitoring.
• Mentor junior team members on AI engineering, experimentation, and evaluation practices.

Skills

Python 3.11+

Async IO

Pydantic

AI/ML exposure

LLMs/Prompt Eng

RAG

Vector search

OpenSearch

Git workflows

CI/CD

Testing (pytest)

Code quality tools (ruff)

Mypy

Tools

Docker

CI/CD tooling

pytest

Ruff

Mypy

Git

OpenSearch

GraphRAG

Vector DBs

Job description

Hiire is supporting Siemens Mobility in its search for a Senior Backend Engineer to join a team building enterprise-grade AI solutions that directly impact critical business operations and workflows.

This is an opportunity to work in a highly technical and multidisciplinary environment where AI, software engineering, and product thinking come together to create scalable solutions for real-world problems. We are looking for someone with a hands‑on mindset, strong production focus, and experience turning AI prototypes into robust and reliable systems.

This is a Hybrid opportunity in Lisbon with a high level of impact.

What You’ll Do

• Collaborate closely with engineering, operations, and business stakeholders to understand workflows, identify pain points, and design AI-driven solutions with measurable impact.
• Translate complex requirements into scalable AI-enabled services and technical concepts.
• Contribute directly to the design and architecture of systems powered by LLMs and retrieval technologies.

Build AI Systems for Production

• Develop and maintain scalable, production-grade AI services focused on: LLMs, RAG pipelines, Hybrid retrieval, Semantic search, Vector search, Agentic workflows
• Build backend APIs, data pipelines, and integrations while ensuring reliability, observability, and engineering best practices.
• Own the full development lifecycle: architecture, implementation, testing, deployment, and monitoring.

AI Evaluation, Prompt Engineering & Data Quality

• Design rigorous evaluation strategies for AI output quality, retrieval accuracy, and model behavior.
• Treat prompt engineering as an engineering and experimentation discipline.
• Ensure high standards for data quality and contextual grounding across AI systems.
• Mentor junior team members on AI engineering, experimentation, and evaluation practices.

What We’re Looking For

• At least 5+ years of experience in Backend Development.
• Strong proficiency in modern Python (3.11+), including: async/await, typing, Pydantic.
• Ability to bridge experimental Data Science workflows with reliable and maintainable software engineering practices.
• Experience with: Docker, CI/CD, testing frameworks (pytest), code quality tooling (ruff, mypy), Git workflows and code reviews
• Exposure to AI, NLP, or Information Retrieval.
• Hands‑on experience with: LLMs, Prompt Engineering, RAG, GraphRAG, Vector databases / OpenSearch, AI evaluation pipelines

Nice to Have

• Experience building and operating AI solutions in production and enterprise environments.
• Experience with AWS Bedrock or Azure OpenAI.
• Familiarity with MCP (Model Context Protocol) and modern AI interface standards.
• If you’re looking for an opportunity to work on applied AI in a serious, scalable, and impactful environment, this could be a very exciting next step.