Job description

Transporeon is a SaaS company founded in 2000 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 2022. Transporeon has one of the largest networks of shippers and carriers in Europe, with approximately 1,400 employees: https://www.transporeon.com/en

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.

Main Responsibilities

LLM Application Development: Architect, implement, and optimize Generative AI applications leveraging Large Language Models (LLMs). Quickly learn and adopt agentic frameworks (e.g., 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.

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.

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:
- Guiding and mentoring other engineers
- Providing technical expertise
Experience with cloud platforms (e.g Azure, AWS)
Knowledge of microservices architecture and containerization technologies (e.g., Docker, Kubernetes)
Experience with RESTful APIs and API design principles
Understanding of database management systems (e.g., NoSQL, PostgreSQL)
Proficiency with Git for version control
Version Control Systems:
- GitHub
- Managing code changes and collaborating with other team members
- Maintaining a history of code revisions
Continuous Integration/Continuous Deployment (CI/CD):
- Tools like GitHub Actions
- Integrating the automation into CI/CD pipelines
Problem-Solving and Analytical Thinking:
- Designing efficient automation solutions/frameworks
- Ability to identify and troubleshoot complex software defects
Agile Methodologies:
- Agile methodologies such as Scrum or Kanban
- Planning for Iterative development cycles
- Manage frequent releases
Risk Assessment and Mitigation:
- Ability 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 of 8 to 15 years
Strong proficiency in Python programming language
Minimum 6 months experience working with GenAI applications
Graduated from a premier institute
B.Tech or M.E / M.Tech / M.S. 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