Requirements
Product & Client Ownership Be the day-to-day technical owner on engagements — understand the client's business deeply, shape the product roadmap, and translate ambiguous problems into clear engineering direction. Show up to demos and reviews with the confidence to defend tradeoffs and flag risks early.
Architecture & Judgment Make architectural decisions that hold up at scale. AI can generate code — your job is to decide what gets built, how it fits together, and when to push back. Evaluate tradeoffs, review TRDs, and set the technical direction the rest of the team executes against.
Fullstack Execution Ship backend services, APIs, database schemas, and user-facing features end-to-end. Use AI-assisted tools (Cursor, Claude Code, Antigravity) to move at the speed of a small team without cutting corners on quality.
Platform & Reliability Own cloud infrastructure, CI/CD, and production systems. Define how the team monitors, debugs, and responds to incidents. If something breaks at 2am, you've already thought about it.
AI & Automation Drive AI adoption in products — LLM APIs, RAG pipelines, agentic workflows. Push for automation across client and internal workflows. Know what these tools are good at and, more importantly, where they fail.
Raising the Bar Be the judgment layer for junior engineers who are moving fast with AI tools. Review code for what matters — not style, but correctness, scalability, and whether the author actually understood what they shipped. Run knowledge-sharing sessions. Onboard people well.
3–5 years of professional engineering experience with production systems you've owned end-to-end.
Active user of AI IDEs (Cursor, Claude Code, Antigravity, or similar).
Demonstrated system design ability — you've made architectural decisions and can evaluate trade-offs.
Good exposure to cloud platforms and deployments.
Familiarity with observability and monitoring tools — you can track down issues and identify bottlenecks.
Deep backend proficiency: API design, databases, microservices, distributed systems, event-driven architecture, and message brokers.
Worked with at least two of REST, GraphQL, or gRPC in production.
Eye for design — you care about the experiences you build for users.
High rate of learning — you figure things out fast.
Cloud architecture experience (AWS, GCP, Azure) with containerisation and orchestration.
Familiarity with AI/ML: prompt engineering, embeddings, agent frameworks (LangChain, CrewAI, LangGraph).
Experience with automation and workflow tools (n8n, Make, Zapier).
Benefits
Mentorship: Work next to some of the best engineers and designers — and be one for others.
Freedom: An environment where you get to practice your craft. No micromanagement.
Comprehensive healthcare: Healthcare for you and your family.
Growth: A tailor-made program to help you achieve your career goals.
A voice that is heard: We don't claim to know the best way of doing things. We like to listen to ideas from our team.
Skills Required
- 3–5 years of professional engineering experience owning production systems end-to-end
- Active use of AI IDEs such as Cursor, Claude Code, Antigravity, or similar
- Demonstrated system design ability and experience making architectural tradeoffs
- Exposure to cloud platforms and deployments
- Familiarity with observability and monitoring tools
- Deep backend proficiency in API design, databases, microservices, distributed systems, event-driven architecture, and message brokers
- Production experience with at least two of REST, GraphQL, or gRPC
- Eye for design and concern for user experiences
- High rate of learning and ability to solve problems quickly
- Cloud architecture experience with AWS, GCP, or Azure, including containerization and orchestration
- Familiarity with AI/ML, prompt engineering, embeddings, or agent frameworks such as LangChain, CrewAI, or LangGraph
- Experience with automation and workflow tools such as n8n, Make, or Zapier
What We Do
Our portfolio? It's on your phone. Wednesday works with digital-first businesses, helping them solve some of their most challenging engineering problems. We are known for our work in these areas: - Data Engineering: Using DataOps principles, we build data pipelines that are cost-effective, performant, and allow you to make strategic decisions. - Generative & Applied AI: We use large language models and your proprietary data to build data-centric intelligent apps for your customers. - App Development: We use our expertise in strategy, product development & design to build web, mobile, TV & IoT Applications. We offer our expertise through these services: - Launch -> https://www.wednesday.is/servicing/launch - Catalyse -> https://www.wednesday.is/servicing/catalyse - Amplify -> https://www.wednesday.is/servicing/amplify - Control -> https://www.wednesday.is/servicing/control Have an engineering problem we can solve. Book some time here: https://calendly.com/wednesday-sol/lets-talk. Want to work at Wednesday? Write to us here: [email protected] Just browsing? Take a look at our company deck here: https://www.dropbox.com/scl/fi/68l7ujqkh0rhv5gbmp23l/Company-Profile-Wednesday-Solutions.pdf?rlkey=krdrhciurpu46l1oqe5obbk7j&dl=0









