The Role
Build and operate AI-native agentic systems for clients, including tools, context, memory, planning, orchestration, guardrails, human oversight, and multi-agent workflows. Develop evaluations to measure quality, regressions, cost, drift, and correction rates. Improve agent-assisted development workflows while contributing across backend, frontend, cloud infrastructure, governance, and data pipelines. Work directly with clients, ship incrementally, test with users, and adapt solutions based on feedback.
Summary Generated by Built In
About the role
What you will do
What you bring
Why this role might be interesting for you
Practicalities
How to apply
We build AI-native software for clients: systems where agents do real work, not systems with a chat window bolted onto the side. We are looking for an AI Software Engineer whose home ground is the agentic layer, meaning tools, context, memory, orchestration, and the evaluations that tell you whether any of it actually works.
Two things define this role. First, agents are what we build: the core of most client systems we deliver is an agentic workflow. Second, agents are how we build: we develop with coding agents, skills, and orchestrators as the default way of working, and part of your job is making that way of working faster and more reliable for everyone around you.
You will ship early and learn from real use. That means rapid discovery, small real versions built to test a hypothesis, and a willingness to drop last week's idea when the feedback says so. It also means working close to the client and the people who use what you build, rather than at a comfortable distance from them.
Build agentic systems as the core of client software
- Design and build agentic workflows: tool design, context engineering, memory, planning, and orchestration, including multi-agent setups when the problem genuinely calls for them.
- Decide where the agent ends and deterministic software begins. Not everything should be an agent, and knowing the difference is a large part of the job.
- Design the guardrails and human oversight a system needs to be trusted in production, and treat cost, scalability, and trustworthiness as design questions rather than things to fix later.
Build and run the evaluations
- Set up evals that test quality, catch regressions, and track performance against cost: accuracy, drift, correction rate, quality gating.
- Treat evals as part of the system, not a report produced at the end. If we cannot measure whether the agent got better, we do not know whether it did.
Build the way we build
- Set up the skills, harnesses, subagents, and context a project needs, and shape a development workflow where agents do a large share of the implementation and humans stay firmly responsible for the result.
- Keep improving that workflow as models and tooling change, which at the moment happens roughly monthly.
You do not need every item below. You should be confident in several and willing to grow into the rest.
Agentic engineering
- Hands-on experience building agentic systems: tool design, context, memory, planning, orchestration. Your opinions on these come from things breaking in real projects, not only from reading about them.
- Practical experience building and running AI evaluations, and the judgement to weigh quality against cost.
- Daily fluency with coding agents (Claude Code, Codex, Cursor, or similar) that goes well past prompting: skills, subagents, parallel runs, and a working sense of what to delegate and what to verify yourself.
Software engineering
- Solid experience with at least one major cloud (Azure, GCP, or AWS), including setting up infrastructure, access, and governance.
- Enough backend and frontend experience to take a real system from architecture to interface without needing each piece handed to you as a finished spec.
- Practical experience with data pipelines: moving and synchronising data, including at larger scale.
Consulting skills and mindset
- Comfortable being close to the client and the people who will actually use what you build.
- Able to read a client's business context and users' needs well enough to make good calls without a full specification in hand.
- Willing to ship early, test with real users, and change direction when new information tells you to, rather than defending a plan.
- Tolerant of ambiguity and of things being unfinished.
- Straightforward and easy to work with, in a small, evolving company.
Why this role might be interesting for you
You'll own real pieces of the stack, work directly with clients, and get to define how AI-native development actually works here, we're still figuring a lot of this out, even ourselves.
Practicalities
- Location: You must be based in Finland and have a valid work permit in Finland.
- Office presence: This is a hybrid role so we’ll expect you to come into our Helsinki office roughly once a week. Client site presence is subject to project and client needs.
- Salary: we have a salary range per role based on experience. We're happy to talk about this early rather than late.
How to apply
We're building a team with a genuinely wide range of backgrounds and ways of thinking. If you're on the fence about whether you fit, we'd rather you applied and let us make that call together.
If this sounds like you, send us your CV and we're happy to tell you more! We review applications continuously.
Skills Required
- Hands-on experience building agentic systems involving tool design, context, memory, planning, or orchestration
- Practical experience building and running AI evaluations, including weighing quality against cost
- Daily fluency with coding agents such as Claude Code, Codex, Cursor, or similar, including skills, subagents, and parallel runs
- Solid experience with at least one major cloud platform: Azure, GCP, or AWS
- Experience setting up cloud infrastructure, access, and governance
- Backend and frontend software development experience sufficient to build a complete system from architecture through interface
- Practical experience building data pipelines for moving and synchronizing data at scale
- Ability to work directly with clients and understand business context and user needs
- Willingness to ship early, test with real users, adapt direction based on feedback, and work effectively with ambiguity
- Based in Finland with a valid work permit in Finland
- Ability to work hybrid from the Helsinki office approximately once per week
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The Company
What We Do
Renessai is a strategic AI consultancy based in Helsinki, Finland. Founded in 2024, the company helps organizations navigate AI hype by combining strategy, change leadership, and technical expertise to create measurable business value. They work with leadership teams to audit AI capabilities, prioritize use cases, and ensure concrete outcomes, rather than selling software or technology products.
