Role – Lead AI Engineer

Technology – AI/ ML, Gen AI, Data Science, Poly Cloud – Azure, AWS, GCP

Location – Zurich, Switzerland

Compensation – Competitive (including bonus)

Job Description

Today, the corporate landscape is dynamic and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where ideas can flourish and where you are empowered to move forward as far as your ideas will take you.

At Infosys, we assure that your career will never stand still, we will inspire you to build what’s next and we will navigate further together. Our journey of learnability, values and trusted relationships with our clients continue to be the cornerstones of our organization and these values are upheld only because of our people.

Your role

In the role of a Lead Consultant within Topaz Unit, you will be one of the pillars shaping the Gen AI/ Agentic AI ecosystems for our esteemed clientele in Europe. You will play a vital role in researching AI trends, designing and defining AI models and frameworks, carving out solutions specific to client needs and driving efficiencies and business benefits. In the process, you will also be collaborating and working closely with business, product and engineering teams, across geographies. You will be pivotal to problem definition and discovery of the overall solution and guide teams on project processes, deliverables. You will anchor business pursuit initiatives, client training, in-house capability building. You will be part of a learning culture, where teamwork and collaboration are encouraged, excellence is rewarded, and diversity is respected and valued.

Required

• Experience of solutioning in Gen AI, Agentic AI, classic ML and automation space
• Experience and good understanding of Prompt engineering, RAG pipelines, Supervised/ unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability
• Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS).
• Experience in architecting and scaling GenAI chatbots
• Experience in Agentic AI solutions. Good knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in at least 1 Hyperscaler
• Design AI interventions (GenAI, Agentic AI, ML) for application support, monitoring, and business ops.
• Good understanding of Responsible AI principles
• Ability to transform business problems into analytical solutions, fostering cross functional collaboration between various stakeholders like business, data science and engineering and building integrated solutions
• Strong articulation, stakeholder management and consulting skills
• Experience working on client proposals – RFI/ RFP/ Orals stages
• Experience in solution presentations to client stakeholders; conduct demos and workshops.
• Experience leading team of AI/ software engineers
• Experience driving productivity and cost optimisations
• Skills: Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain,Langsmith/Langfuse, Gen AI / Agentic AI , Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI) , MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes).

Preferred

• Delivered AI projects within Agile frameworks
• Experience on Model Feedback Analysis, topic modelling, sentiment analysis
• Knowledge of AgentOps and OpenTelemetry
• Understanding of Network Security Concepts, Network Telemetry and Analytics
• Understanding of Cloud computing and Virtualization
• Exposure to APM/Observability tools (Dynatrace, AppDynamics, Datadog, Splunk etc)
• Exposure to onshore-offshore model working with professionals spread across the globe
• Participation in AI events, workshops and summits

Personal

Besides the professional qualifications, we respect and place equal importance to the candidate’s personality which facilitates success in customer environments. Few traits we look for are:

• High analytical skills
• A high degree of initiative, flexibility and adaptability
• High customer orientation
• Good team engaging skills
• Quality awareness
• Good verbal and written communication skills
• Transparency and Integrity
• Taking accountability