Senior AI Architect

Infosys; Oslo; On-site; NOK 1,000,000 - 1,400,000; Full time

Job summary

Infosys Oslo seeks Senior Architect/Consultants to lead Generative AI Technologies, shaping strategy, selecting models, and delivering enterprise-grade solutions. You will collaborate across teams to meet customer needs and business goals while ensuring scalable, secure architectures.

Ideal candidates bring deep Gen AI expertise, agentic design experience, RAG know-how, and hands-on proficiency with modern tooling and cloud platforms in a fast-paced environment.

Qualifications

• Experience leading Generative AI technology programs in enterprise settings.
• Ability to design end-to-end Gen AI and agentic systems with MCP-based integration.
• Strong knowledge of RAG, embeddings, vector databases, and evaluation.

Responsibilities

• Lead the Generative AI Technologies team to deliver enterprise-scale solutions.
• Architect model selection, tooling, and MCP-based connectivity across systems.
• Collaborate with cross-functional teams to meet customer goals.

Skills

Generative AI

Agentic AI

MCP & Interop

RAG Knowledge

LLMOps & Responsible AI

ML Fundamentals

Python & ML Frameworks

Architectural Design

Education

Bachelor's degree in a relevant field

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Cloud AI platforms

Job description

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

Location – Oslo, Norway

Business Unit – TOPAZDLVRY

Compensation – Competitive (including bonus)

Job Summary

We are seeking a highly skilled and experienced Senior Architect/Consultants to lead our Generative AI Technologies team. The ideal candidate will have a deep understanding of Generative and Agentic AI, LLMs, retrieval-augmented generation (RAG), machine learning, and modern interoperability standards such as the Model Context Protocol (MCP), along with a proven track record of architecting and implementing innovative, enterprise-scale solutions. As a Senior Architect/Consultant, you will play a pivotal role in shaping our Generative AI strategy, selecting appropriate models and technologies, and collaborating with cross-functional teams to deliver cutting-edge solutions that meet customer requirements and business objectives.

Primary Skill Set

• Generative AI Expertise: In-depth knowledge of modern Generative AI techniques and foundation models, including transformer-based Large Language Models (LLMs), diffusion models, and multimodal models, as well as earlier architectures such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders). Experience across text, code, image, and multimodal generation is essential. Conversant with modern Gen AI development techniques and tooling such as advanced prompt engineering, structured outputs, function/tool calling, and orchestration frameworks like LangChain, LangGraph, LlamaIndex, and Semantic Kernel. Hands-on exposure to both API-based (e.g., Claude, GPT, Gemini) and open-source (e.g., Llama, Mistral) LLM-based solution design.
• Agentic AI & Multi-Agent Architecture: Deep expertise designing autonomous and multi-agent systems that reason, plan, and act using tools. Command of agentic design patterns (e.g., ReAct, planning, reflection, tool use, human-in-the-loop) and agent frameworks such as LangGraph, CrewAI, MAF, the OpenAI Agents SDK, and Google’s Agent Development Kit (ADK). Proven ability to architect reliable agentic workflows with memory, state management, orchestration, and safe multi-step task execution at scale.
• Model Context Protocol (MCP) & Interoperability: Strong working knowledge of the Model Context Protocol (MCP) for standardized, secure connectivity between LLMs/agents and enterprise tools, data sources, and systems. Ability to architect, build, and govern MCP servers and clients and to work with MCP primitives such as tools, resources, and prompts. Awareness of related interoperability standards (e.g., agent-to-agent communication) for composing scalable, enterprise-grade agentic ecosystems.
• Agent Skills & Extensibility: Experience extending agent capabilities through modular, reusable skills—packaged instructions, scripts, and resources (e.g., SKILL.md-style capability modules) loaded on demand via progressive disclosure. Ability to define standards for custom tools, connectors, and skills that let agents perform specialized, domain-specific tasks reliably, securely, and consistently across teams.
• Retrieval-Augmented Generation (RAG) & Knowledge Architecture: Expertise architecting RAG and knowledge-grounded systems—chunking strategies, embeddings, vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), hybrid search, reranking, and retrieval evaluation. Familiarity with advanced patterns such as GraphRAG and agentic RAG to maximize factual grounding and minimize hallucination in production.
• LLMOps, Evaluation & Responsible AI: Experience operationalizing LLM and agentic systems at scale—evaluation harnesses and metrics for quality, groundedness, and safety; observability, tracing, and monitoring (e.g., LangSmith, LangFuse); guardrails and red-teaming; and continuous optimization of accuracy, cost, and latency. Understanding of AI governance, security, privacy, bias/fairness, and emerging AI regulation.
• Machine Learning Mastery: Profound understanding of machine learning principles, algorithms, and frameworks. Able to design and implement models, optimize performance, and manage training pipelines effectively.
• Technical Proficiency: Proficiency in programming languages commonly used in AI development, such as Python, TensorFlow, PyTorch, or similar tools, along with modern LLM/agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon Bedrock, Azure OpenAI / AI Foundry, Google Vertex AI), vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), containerization and orchestration (Docker, Kubernetes), and distributed computing is advantageous.
• Architecture Design: Ability to design end-to-end Generative and Agentic AI architectures that encompass data preprocessing, model selection, RAG pipelines, agent orchestration, MCP-based tool and system integration, guardrails, training/inference pipelines, and deployment strategies. Strong grasp of scalable, reliable, secure, and cost- and latency-efficient system design for enterprise-grade AI.

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
• Quality awareness
• Good verbal and written communication skills
• Transparency and Integrity
• Taking accountability

Topaz Centre of Excellence is the Central AI and automation evangelisation unit at Infosys. Our vision is to enable Infosys towards delivering exponential value to customers through AI driven differentiation across all horizontal and vertical services, leveraging our internal as well as our partner capabilities. We enable Infosys towards an AI First Organization and to establish Infosys as a Market Leader in AI and Gen AI space. We help clients define roadmaps and realize productivity gains and business benefits through Automation, AI and Gen AI. Our AI-first set of services, solutions and platforms using generative AI technologies help amplify the potential of humans, enterprises and communities to create value from unprecedented innovations, pervasive efficiencies and connected ecosystems. We bring the advantage of 12,000+ AI assets, 150+ pre-trained AI models, 10+ AI platforms steered by AI-first specialists and data strategists, and a ‘responsible by design’ approach that is uncompromising on ethics, trust, privacy, security and regulatory compliance.

About Infosys

Infosys is a global leader in next-generation digital services and consulting. We enable clients in 59 countries to navigate their digital transformation.

With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer clients, in 59 countries, as they navigate their digital transformation powered by cloud and AI. We enable them with an AI-first core, empower the business with agile digital at scale and drive continuous improvement with always-on learning through the transfer of digital skills, expertise, and ideas from our innovation ecosystem. We are deeply committed to being a well-governed, environmentally sustainable organization where diverse talent thrives in an inclusive workplace.

All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer