Senior Full-Stack Developer – Angular, Python and AWS Simulation

Project overview

Application/Offer Deadline 05.11.2026, 16:00

Project Framework Conditions

Project details

Frankfurt am Main; presence for technical coordination, possibly other locations in Germany

01.01.2027–31.12.2027; approx. 11.99 months

Scope: 216 PT of which 171 remote, 45 Onsite = 79.17% remote

Utilization: Average approx. 4.14 days/week

Onshore: Germany

Language / Required Language Level: German – Native speaker

Conditions – Mandatory Information for Candidates:

For further processing of your application, this information is mandatory: Please state your desired billing method and your hourly or daily rate, separated for Remote and Onsite. Also indicate whether travel expenses are included or charged separately. If charged separately, please state the amount or the basis for calculation.

1.1 Project/Process Context

Further develop an AWS-based simulation platform for microscopic, network-wide railway operations simulations. Analyze timetable quality, capacity, delays, and construction impacts using infrastructure, timetable, and operational data. Funding project.

1.2 Project Structure

Agile DevOps team with Sprints and Program Increments. Mono-repository, one merge request per end-to-end feature, functional reviews, and automated build/test/deployment pipelines in GitLab. AI development in agent mode is a daily requirement. GitLab, virtual desktop, Kiro-CLI, and provided user account are mandatory; necessary tools/licenses will be provided.

3.1 Scope

4.1 Must-Have Requirements – 100% Mandatory to Fulfill

M1: Proven professional frontend development predominantly with Angular, key role in module/component interfaces and state management strategy; experience level Senior (> 5 years).

M2: Architectural further development of established applications across frontend/backend: module/component interfaces, dependency directions, layer boundaries, resolution of architecture violations; experience level Senior (> 5 years).

M3: Practical agent-based AI software development in agent mode, not just code auto-completion, e.g., Kiro, Claude Code, Cursor, OpenCode; 2 references.

M4: Python web APIs with FastAPI/Pydantic, relational data storage via SQLAlchemy including schema migrations; 2 references.

M5: Development and implementation of algorithms for railway freight transport planning; 1 reference.

4.2 Should-Have Requirements

Proof of S1–S6 each by number of references.

S1 (25%): WebGL maps/geospatial data visualization of large dynamic datasets and interactive map object editing (selection, moving, geometry/attribute editing) with Deck.gl, MapLibre, Three.js; 2.

S2 (25%): Complex, performant tables of large datasets with AG Grid; 2.

S3 (20%): Complex interactive editors/forms for structured data, dynamic forms, validation, dirty/undo handling, and conflicts during simultaneous editing; 2.

S4 (10%): Performant display of large datasets with Plotly.js, especially time series/interactive charts; 2.

S5 (10%): Proven depth in productive Python web services with FastAPI (or comparable): authentication, role/permission-based authorization (OIDC/JWT, API Keys), versioned schema migrations on a running relational database; 2.

S6 (10%): UI according to design system with Figma, design tokens/variables, and integration of design/code, e.g., Figma Code Connect; 1.

• Conditions / Billing Method (Hourly or Daily Rate)
• Hourly Rate Remote (EUR/hour) and Hourly Rate Onsite (EUR/hour)
• Or Daily Rate Remote (EUR/day) and Daily Rate Onsite (EUR/day)
• Travel Expenses
• Maintain/extend Angular 22 with Standalone Components and Signal State Management; develop KPI-based analysis views for time series, maps, tables, and graphical timetables using GraphQL.
• Develop WebGL maps with Deck.gl for infrastructure/train movements and editors for timetable, infrastructure, master, and model data; maintain reusable UI components according to the design system.
• Connect REST/GraphQL and Protobuf; reduce architecture violations, migrate Leaflet to Deck.gl, increase test coverage, and implement unit/E2E tests.
• Develop/maintain Python REST endpoints with FastAPI, Pydantic, SQLAlchemy, and Alembic/PostgreSQL schema migrations. Extend GraphQL API with Ariadne for large result sets via Athena/Parquet.
• Further develop serverless import/ETL/simulation pipelines with AWS Lambda, Batch, S3, and Glue; implement features end-to-end across frontend, API, and pipeline.
• Start: 2027-01
• Duration: 12 Monate
• Remote: hybrid
• Location: Frankfurt am Main, Deutschland, DE
• Languages: German