GenAI Developer

Redeploy AB; Stockholms kommun; Hybrid; SEK 600,000 - 800,000; Full time

Benefits offered by this job

30 days vacation

Hybrid work and flexible hours

Private medical insurance

Pension (ITP1)

Wellness allowance 5 000 SEK

Free choice of tools and tech

Free breakfast, soda and snacks

Yearly gatherings and AWs

Job summary

Redeploy AB is hiring a GenAI Developer to design and build production-grade AI systems in Stockholm. The role includes ownership of the AI application layer, turning business challenges into working solutions, and collaborating with cross-functional teams. Ideal candidates will have strong skills in Python, RAG architectures, and stakeholder management. The company offers a hybrid work model and various perks to foster growth and flexibility.

Qualifications

• Strong requirements engineering and stakeholder management skills.
• Strong Python skills and solid software engineering fundamentals.
• Production experience with RAG architectures.

Responsibilities

• Own the AI application layer end-to-end.
• Turn business problems into working use-cases.
• Collaborate closely with Data and Platform Engineers.

Skills

Requirements engineering

Stakeholder management

Python

Software engineering fundamentals

Production experience with RAG architectures

Agentic frameworks (LangChain, AutoGen)

Azure AI Services

Lightweight front-end interfaces

Tools

React

MLOps tools

Job description

TL;DR

You design and build production‑grade RAG and agentic AI systems end‑to‑end, consulting across the Nordics with clients from financial services to manufacturing. You work in cross‑functional delivery teams and shape solutions before they’re defined. Freedom to grow and certifications are part of the culture.

What you’ll do

As a GenAI Developer you own the AI application layer end‑to‑end: the systems that ingest, retrieve, reason, and respond, plus lightweight interfaces for users. You turn business problems into working use‑cases, from gathering requirements and aligning stakeholders to shipping production systems people actually use. You collaborate closely with Data and Platform Engineers; your layer is where the model meets the business problem and where users meet the product.

Examples of your work

Production RAG system for a financial services client, enabling teams to navigate regulatory documentation with generative AI. An agentic AI solution in the FinOps space that applies LLM reasoning to cloud cost data, exceeding rule‑based tooling. AI capability building at enterprise clients with use‑case workshops, requirements definition, and architecture advisory on agents and coding tools for senior technical audiences.

The bar for “done” is high: production‑grade, observable, secure and in active use.

What you get

Assignments that give you rapid growth: every 6‑18 months you step into a new engagement, learning a new industry, new architecture decisions and new stakeholders. You’ll face more distinct technical challenges in two years here than most engineers see in five.

Work in a technically demanding space—agentic AI in enterprise environments—where problems are not yet solved and you’ll be among those solving them.

Your direction is yours. Whether you want to dive deep technically into enterprise AI architecture or lead client engagements and drive use‑cases from discovery to production, both paths are real and equally valued.

People who make you better

The team is truly passionate about technology, working not only for a job but for a commitment to keep moving forward. Engineers who go deep because they want to, follow the space obsessively, and get restless when things stop moving. That’s what keeps the company ahead.

The perks

• 30 days vacation
• Hybrid work and flexible hours
• Private medical insurance
• Pension (ITP1)
• Wellness allowance 5 000 SEK
• Free choice of tools and tech
• Free breakfast, soda and snacks
• Yearly gatherings and AWs
• Team interests outside work: gaming, food, running, padel, golf, football, cycling

Who you are

You care that AI systems actually work, not just run, and you instinctively look for failure modes before production. You care about how users interact with it and consider a use‑case incomplete until it works end‑to‑end, interface included.

You may come from full‑stack engineering or a traditional ML/Data background. What matters is that you’re already building AI solutions—side projects, POCs or deep dives—curiosity is given, and you act on it.

You enjoy being close to end‑users, running requirements workshops, clarifying what stakeholders truly need, and explaining why a retrieval pipeline underperforms, all with clear communication.

What you bring

• Strong requirements engineering and stakeholder management skills; keep technical and non‑technical audiences aligned from problem definition to delivery
• Strong Python skills and solid software engineering fundamentals: clean code, testing, version control, system design
• Production experience with RAG architectures: chunking strategies, embedding models, vector search, hybrid retrieval, reranking, and retrieval evaluation
• Hands‑on experience with agentic frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI, including tool use, memory management, and multi‑agent orchestration
• Experience with Azure AI Services or Azure OpenAI, including integration across Azure services in production environments
• Ability to build lightweight front‑end interfaces for AI applications, enabling prototypes and internal tools to be usable beyond the terminal
• Strong plus: multi‑agent architecture design, front‑end development skills (React, Streamlit, or similar), containerization and MLOps awareness, experience in regulated industries, Azure AI‑102 certification, prior consulting experience, Swedish language skills

About Redeploy

Redeploy is where cloud, data, and AI converge in production. We help Nordic enterprises design, build, and operate modern tech platforms and AI solutions that are secure, scalable, and ready for production. Engineers at heart, we work hands‑on across Azure, AWS, and Databricks from strategy to operations.