Digital Development Platform > Autonomous Flows > Autonomous Flows Advisors
At the core of Data AI organization, the AI/ML Chapter serves as the capability home for AI/ML, supporting craft excellence, skills development and scalable delivery practices across Vestas. With a global footprint spanning India and Denmark, the team partners closely with product owners and engineering teams to build and scale AI/ML solutions embedded in digital products across the value chain.
The chapter focuses on building and scaling AI/ML capabilities for high-value and autonomous flow use cases, providing consistent know-how across product areas, ensuring readiness for emerging paradigms such as LLMs and agentic AI, and enabling scalable delivery through a balanced mix of internal capability development and strategic partnerships. Through solid engineering, data-centricity, and close business collaboration, the team advances AI/ML delivery practices and enables impactful solutions that improve visibility, optimization and innovation across the enterprise.
Responsibilities
- As part of the product team, you will collaborate with product owner, ML engineers, application developers and business SMEs to develop and scale GenAI and agent-based capabilities within digital products. This role focuses on active development, learning, and contributing to valuable AI solutions
- Contribute to the design, development and deployment of GenAI and agentic systems supporting reasoning, planning, and semi-autonomous workflows
- Build and enhance components of GenAI solutions using LLMs, RAG pipelines, prompt engineering and tool integration
- Develop intelligent workflows using techniques such as prompt engineering, context orchestration and function/tool calling
- Integrate GenAI capabilities into enterprise applications using APIs, microservices, and containerized environments
- Collaborate with senior AI engineers to implement scalable, reliable GenAI systems and follow established design patterns and standards
- Participate in end-to-end delivery of GenAI initiatives, contributing to development, testing and deployment
- Continuously learn and adopt best practices in GenAI, NLP, and agentic systems development
Qualifications
- AI/ML Solutions Experience
- Bachelors or Masters degree in Computer Science / Engineering / Data Science / or similar specialization
- 6+ years of experience in AI/ML, software engineering, data or analytics, focusing on digital solutions development
- 2-5 years of core experience in AI/ML solution development, ML engineering, with a focus on NLP and applied GenAI systems
- Practical experience with LLM ecosystems (e.g., OpenAI, Azure OpenAI, open-source models), including prompt engineering and basic context design
- Practical experience with RAG architecture, embeddings or vector databases
- Experience building and integrating applications using APIs, microservices or containerized environments
- Familiarity with software engineering best practices (version control, testing, CI/CD basics)
- Exposure to agentic workflows, including tool usage, chaining, or multi-step reasoning
- Familiarity with LLM evaluation concepts and basic understanding of LLMOps practices such as monitoring, versioning, and cost awareness
Competencies
- LLM Systems Engineering
- Ability to contribute to building scalable and reliable GenAI systems with focus on performance and maintainability o Understanding of standard design patterns and engineering practices for LLM-based applications
- Familiarity with deploying and integrating GenAI solutions into production environments
- GenAI Agentic Solution Development
- Practical experience in developing GenAI and agent-based solutions for structured workflows and assisted decision-making
- Working knowledge of techniques such as RAG, prompt engineering and tool integration
- Ability to implement intelligent workflows combining human-in-the-loop and automated processes under guidance
- Foundational AI/ML Software Engineering
- Solid foundation in ML concepts and software engineering principles for building maintainable systems
- Experience developing and integrating services using APIs, microservices and modern engineering practices
- Proficiency in leveraging AI-assisted development tools (e.g., GitHub Copilot, Claude Code) to improve productivity and code quality
- Global Collaboration Enablement
- Ability to collaborate effectively within distributed teams across geographies
- Solid teamwork skills working with senior engineers and cross-functional stakeholders
- Demonstrates a continuous learning mindset with interest in GenAI, NLP and agentic systems
Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.