PRINCIPLE PYTHON ENGINEER FOR GENERATIVE AI BACKEND DEVELOPMENT

Main Responsibilities LLM Application Development.
Architect, implement, and optimize Generative AI applications leveraging Large Language Models (LLMs).
Quickly learn and adopt agentic frameworks (e.
., LangChain, LangGraph) to orchestrate LLM-based agents.
Working with RAG frameworks.
Use techniques such as chunking, hybrid search, query translation, similarity search, vector DBs, evaluation metrics, and ANN algorithms.
Monitoring performance.
Using observability services such as Datadog and Databricks for LLM Observability and analytics.
Keep track of latest research.
Given that this is a fast evolving field, it’s important to keep track of the latest advancements in fine-tuning, RLHF, and prompt engineering advancements such as DSPy.
System Design & Architecture.
Translate high-level product requirements into scalable, modular software designs that adhere to modern design principles, microservices architecture, and cloud-native best practices.
Testing & Integration.
Develop comprehensive test suites (unit, integration, and end-to-end) to ensure code quality and ensure that automated tests cover a high percentage of the codebase.
Integrate solutions across systems, perform bug fixes, and conduct rigorous quality assurance.
Collaboration & Mentorship.
Collaborate with cross-functional stakeholders, including business analysts, product managers, and global development teams.
Mentor junior engineers, guiding them through LLM-based solution design, implementation, and deployment.
Agile Delivery.
Work in an agile environment, planning and executing sprints, meeting strict deadlines, and efficiently handling production issues across multiple time zones.
CI/CD & Version Control.
Employ CI/CD pipelines (GitHub Actions or similar) and maintain code versioning in GitHub for seamless, frequent releases.
Skillsets Strong proficiency in Python programming language Minimum 6 months experience working with GenAI applications Strong communication skills since we work with a global team Leadership and Mentoring.
uiding and mentoring other engineers Providing technical expertise Experience with cloud platforms (e.
Azure, AWS) Knowledge of microservices architecture and containerization technologies (e.
., Docker, Kubernetes) Experience with RESTful APIs and API design principles Understanding of database management systems (e.
., NoSQL, PostgreSQL) Proficiency with Git for version control Version Control Systems.
itHub Managing code changes and collaborating with other team members Maintaining a history of code revisions Continuous Integration/Continuous Deployment (CI/CD).
ools like GitHub Actions Integrating the automation into CI/CD pipelines Problem-Solving and Analytical Thinking.
esigning efficient automation solutions/frameworks Ability to identify and troubleshoot complex software defects Agile Methodologies.
gile methodologies such as Scrum or Kanban Planning for Iterative development cycles Manage frequent releases Risk Assessment and Mitigation.
bility to identify and mitigate risks related to software quality Measure how well risks are documented and managed throughout the project Qualifications & Experience Engineering experience in a tier-1 organization for a period o f 8 to 15 years Strong proficiency in Python programming language Minimum 6 months experience working with GenAI applications Graduated from a premier institute B.
ech or M.
/ M.
ech / M.
.
in Computer Science Engineering An impressive performance in any national-level Olympiad or talent search examination would be a valuable asset Presenting a paper at a national-level forum, contributing to open-source projects, and participating in standards bodies would be beneficial additions Key Result Area LLM Solutions Delivery.
Launch production-ready LLM-based agentic applications on schedule, ensuring quality and scalability.
Quality & Automation.
Achieve high-quality daily releases and ensure automated tests cover a high percentage of the codebase.
Risk Management & Reporting.
Proactively identify risks and effectively communicate them to stakeholders.
Maintain transparent and timely reporting of development progress and metrics.
Our Inclusiveness Commitment We believe in celebrating our differences.
That is why our diversity is our strength.
To us, that means actively participating in opportunities to be inclusive.
Diversity, Equity, and Inclusion have guided our current success while also moving our desire to improve.
We actively seek to add members to our community who represent our customers and the places we live and work.
We have programs in place to make sure our people are seen, heard, and welcomed and most importantly that they know they belong, no matter who they are or where they are coming from.
Job Location.
Remote Transporeon is a SaaS company founded in in Ulm, Germany.
The company provides logistics solutions across several areas, including.
Buying & selling of logistics services Organizing shipment execution Organizing dock, yard, truck, and driver schedules Invoice auditing for logistics services It has grown significantly over the years, reaching €150m in revenue before being acquired by Trimble for $2 billion USD in .
Transporeon has one of the largest networks of shippers and carriers in Europe, with approximately employees.
We are looking for a Generative AI Staff Software Engineers (Remote work) to help build LLM-based agentic applications.
Job Purpose As a Staff Software Engineer specializing in Generative AI, you will design, develop, and maintain cutting-edge LLM-based agentic applications.
This role requires hands-on expertise in frameworks such as LangChain or LangGraph, and techniques including prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning.
In other words, you will be expected to ship deliverables yourself too.
You will build solutions to meet functional requirements for innovative Trimble products, collaborating across global teams and leveraging agile methodologies.
Your work will directly influence the delivery of intelligent, scalable, and robust AI-driven applications.
Moreover, you will be expected to provide non-technical management and overview of the capabilities, the risks and the opportunities related to specific technologies.