Job description
About us:
At our reputed company, we don't just build Vehicles, we create great software. We develop tomorrow's mobility together in our product lines, pushing the digitization of the institution forward.
As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work. IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.
We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the company. Our workplace is anywhere with a fast connection whether remotely at home, at your favorite café, or at our integrated company office.
Key Responsibilities / Job Description
Design and implement end-to-end AI systems including inference pipelines, agent
workflows, and tool-calling architectures
Build and manage context orchestration for LLMs (system prompts, memory, retrieval, and structured inputs)
Engineer latency-aware and cost-efficient fallback strategies across models and providers.
Develop backend services for prompt routing, response handling, and tool execution (Python / Node.js or similar)
Implement observability for AI systems: logging, metrics, tracing, and quality monitoring
Maintain CI/CD pipelines for AI services and ensure safe, repeatable deployments
Design, develop, integrate and deploy AI-powered software solutions into productive, scalable enterprise environments
Translate business and product requirements into robust AI system designs and architectures
Collaborate closely with data scientists, software engineers, product owners, and business stakeholders
Ensure compliance with applicable rules in the areas of data protection, AI governance, and IT security
Document architectures, models, and implementation decisions in a target-group adequate form
Required Skills & Qualifications
2+ years in software engineering, including hands-on experience with AI/ML or LLM systems
Bachelor's/Master's in Computer Science, Data Science, or related fieldExperience with LLMs, prompt engineering, tools, and agent-style architecture
Experience in Agile, product-driven teams
Familiarity with enterprise-scale architectures, DevOps, and CI/CD
Specific Knowledge / Skills
Proficient in Python
Experience with LLMs, NLP, or semantic models
Skilled in fine-tuning and evaluating LLMs, including quality and failure modes
Able to build automated AI pipelines for training, testing, deployment, and monitoring
Familiar with cloud platforms and containers
Analytical thinker; committed to robust, reliable software
Strong communicator with a customer focus
Results-driven, emphasizing scalable, maintainable solutions
Actively follows and adopts new AI advancements
Bonus Points if you have
Experience with LLM APIs such as OpenAI, Claude, or similar providers
Hands-on work with RAG systems, vector databases, and embedding pipelines
Exposure to model safety, guardrails, or responsible AI practices
Technical
Python
SQL / NoSQL
REST APIs and backend integration
LLM-based solution development
Spark / Apache ecosystem
Cloud Computing
GPU orchestration and cost optimization
Containerization (Docker, Kubernetes)
CI/CD and DevOps tooling
Scalable data and AI architectures
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.