Home › Companies › Squer › Senior Software Engineer - Applied AI & Data Products
Senior Software Engineer - Applied AI & Data Products
Squer · München · Hybrid · Active · Personio
Job facts
| Field | Value |
|---|---|
| Company | Squer |
| Title | Senior Software Engineer - Applied AI & Data Products |
| Normalized title | - |
| Department / team | Product, Data & AI / Bewerber |
| Location | München |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Personio |
| Posted / first seen | 2025-11-13 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Squer. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Personio. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Product, Data & AI. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Squer |
| Source | 04024489-fb82-47b5-a682-3dea2aa8dd96 |
| ATS provider | Personio |
Description
Description
Are you excited about building smart, data-driven products using the latest AI technologies? At SQUER, we help our customers unlock the potential of AI through real-world software solutions — not by building custom models from scratch, but by applying LLMs, cloud-native AI services, and smart engineering. Join our Product Delivery Unit and shape how applied AI enhances modern digital products.
Your tasks
Design and build AI-enhanced software products using modern cloud services and frameworks (e.g., Azure OpenAI, AWS Bedrock, LangChain). Apply Large Language Models (LLMs), retrieval-augmented generation (RAG), cognitive services and other technologies to solve real customer problems. Collaborate with product managers, designers, and customer teams to identify where AI adds measurable value. Design scalable data pipelines and APIs that power intelligent features in production-grade environments. Lead technical discussions, mentor peers, and contribute to our applied AI engineering practices.
Your qualifications
Several years of experience in software engineering (e.g., Python, Java, C#, JS/TS, or similar). Hands-on experience applying AI services in real-world applications (e.g., LLMs, NLP APIs, cognitive services). Familiarity with cloud platforms like AWS, GCP or Azure and experience deploying AI-driven features in production environments. Understanding of data processing, APIs, and databases (SQL & NoSQL). Passion for building high-quality software and delivering meaningful user outcomes with AI. Actively use of AI-powered tools (e.g., code assistants, LLM-based workflows) to amplify your productivity and quality Fluency in German and English.
Your Benefits
Why You'll Love Working at SQUER:
Ownership & Responsibility : at SQUER, we believe in empowering our team. In our flat hierarchies, your ideas and actions matter more than titles. Take the reins, make an impact and grow with us. Learn & Grow : Tap into a € 5.000 annual training budget to sharpen your skills and take advantage of our in-house Leadership Academy. Join and be part of our active tech community through meetups, hackathons and training sessions. Get up to 40h/year additional time off for your personal education. Exciting Challenges & Real Impact : Dive into diverse projects where your work truly makes a difference – for our clients and for SQUER. Flexibility for Performance : Benefit from hybrid work options, flexible hours, workations within the EU, and additional vacation days – giving you the freedom to perform at your best. Tailored Tools for Success : Choose your preferred hardware configuration and leverage our suite of AI tools and licenses (Anthropic, OpenAI, and more) to suit your working style. We Value You : Beyond perks and benefits, we offer a competitive annual salary to recognize your exceptional contributions. Be Part of a Thriving Team Culture : At SQUER, collaboration and connection are at the heart of what we do. Through open communication, shared successes, and meaningful team events – including our annual SQUER offsite – we cultivate a culture where everyone feels valued and inspired to grow together. A Perks-Packed Workplace : Work in a central office near Ostbahnhof and enjoy meal vouchers, EGYM Wellpass membership, a free Deutschland-Ticket, JobRad, referral bonuses, Corporate Benefits, and Pluxee employee gifts for special occasions.
Full job record
| Job ID | 2302d3423b9ad3137bc262e5dfdcdd34c403e92f |
| Org ID | 60d78e3d-a1ae-4f74-b976-d9dd47d395d5 |
| Source ID | 04024489-fb82-47b5-a682-3dea2aa8dd96 |
| Board ID | 04024489-fb82-47b5-a682-3dea2aa8dd96 |
| Provider | personio |
| Provider Job Key | 2426224 |
| Title | Senior Software Engineer - Applied AI & Data Products |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | München |
| Department | Product, Data & AI |
| Team | Bewerber |
| Employment Type | full_time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | München |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://squer.jobs.personio.com/job/2426224?language=en |
| Apply URL | https://squer.jobs.personio.com/job/2426224?language=en |
| First Seen At | 2026-05-30 05:39:10Z |
| Last Seen At | 2026-06-06 19:53:32Z |
| Last Checked At | 2026-06-06 19:53:32Z |
| Last Changed At | 2026-05-30 05:39:10Z |
| Inactive At | — |
| Source Posted At | 2025-11-13 11:56:13Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=personio/board=squer.com/date=2026-06-06/2026-06-06T19-53-31-370Z-f7493355aab94e96c70ece0da064995acb2447d7893a371033a18985c8c8a273.json |
Event Fields
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