# Careers — Renessai

We’re a senior team that pairs management-consulting depth with real technical hands. We hire people who think beyond the AI hype.

## Open roles

### Strategy & Transformation Consultant

- **Location:** Helsinki, Finland
- **Work model:** Hybrid
- **Employment type:** Full-time
- **Team:** Strategy & Transformation
- **Apply:** https://jobs.gem.com/renessai-com/am9icG9zdDr0Jwe5BpvaEudvCgGfRtE5

About the role
We are looking for an experienced Strategy & Transformation Consultant to lead our clients transition from initial ideas about AI and data into clear strategies, roadmaps and concrete initiatives that deliver measurable business impact.
You will lead early-phase conversations where AI and data maturity is often low, structure what the client is really trying to achieve, and define a roadmap for success. You will work at the interface of business and technology, from first discussions through to implementation.
We’re open to all experience levels; whether you’ve currently got a couple of years under your belt or you’re already a seasoned pro, we’d love to chat!
What you will do
Lead early-stage AI & data discussions
Work with business leaders whose needs are not yet clearly defined.
Clarify objectives, constraints and expectations, and turn them into structured problem statements and realistic goals.
Facilitate workshops, interviews and working sessions in environments where AI and data maturity vary widely.
Shape AI strategies, operating models and roadmaps
Translate business goals into concrete AI and data initiatives, portfolios and roadmaps.
Define governance and prioritisation to match the client’s maturity and ambition level.
Design operating models, roles and ways of working needed for sustained AI transformation.
Bridge business stakeholders and technical teams
Ensure a shared understanding of goals, scope and constraints, and keep alignment from strategy through execution.
Help clients see where AI makes sense (and where it does not) in the context of their processes, business models and technology.
Support expert-driven sales and case shaping
Join early client meetings to understand the situation and identify where we can create real value.
Co-create proposals, scopes and engagement models that are realistic and outcome-driven
Stay close to implementation and value realisation
Remain engaged as projects move from slides to delivery.
Safeguard strategic intent and business value while technical teams execute.
Develop our AI transformation thinking and offering
Contribute to our methods, frameworks and reference cases around AI-enabled transformation.
Share lessons from client work, and help us refine how we approach AI-enabled business model renewal, process redesign and capability builds.
Push broader transformation themes with clients, not only react to incoming requests.
What you bring
Background and experience
You are likely to have one or more of the following:
Solid experience working at the interface of business and data/AI 
or 
digital transformation.
Background in advisory-type consulting (strategy, digital, data/AI), 
or
Experience in a larger company in at least middle-management roles with responsibility across multiple stakeholders.
Proven track record in leading or owning (digital) transformation.
Especially for less senior applicants: Education that signals strong analytical ability and comfort with complex systems is seen as an advantage (e.g. industrial engineering and management or similar).
Skills and capabilities
You will need to be comfortable with:
Leading early-phase, ambiguous discussions and turning them into clear problems, options and decisions.
Designing AI and data strategies, operating models and roadmaps that fit the client’s context and maturity.
Structuring thinking for others: frameworks, models, simple visuals that help people align.
Navigating complex organisations with multiple stakeholders, interests and clients’ internal politics.
You will likely do well in this role if you prefer honest, content-driven discussions over buzzwords, and if you are willing to say “no” or “not yet” when something does not make sense.
Why this role might be interesting for you
Real influence on what gets sold and built
You will not be “dropped into” predefined boxes. You will be part of the early discussions, help shape what we propose and how we work with clients, and then stay involved when the work starts.
Authentic expert work, not product pushing
We sell through our own expertise and advice, not through rigid offerings that you must push regardless of context.
Blend of strategy and execution
You stay close to the work as it moves from strategy to implementation. The aim is real change in how our clients operate, not only decks.
Long-term, strategic client relationships
There is clear potential for long-running partnerships where we become a strategic AI and data partner, not just a one-off supplier.
Room to shape your own path
You can influence which industries you focus on and how we develop our AI/data transformation offering. There is space to build on your strengths.
Practicalities
Location:
 You must be based in Finland and have
 a valid work permit in Finland.
Office presence:
 Ability to visit our Helsinki office roughly once a week (sometimes more depending on client needs).
How to apply
If this sounds like a good fit, send us your CV and we’re happy to tell you more!
We review applications continuously.

### ML/AI Engineer

- **Location:** Helsinki, Finland
- **Work model:** Hybrid
- **Employment type:** Full-time
- **Team:** Machine Learning and AI
- **Apply:** https://jobs.gem.com/renessai-com/am9icG9zdDrcVtJmi-dOh20suZ3qKBi-

About the role
We are looking for a Senior ML/AI Engineer to design, build and productionise AI systems that solve concrete business problems for our clients.
You will lead discovery for AI use cases, assess feasibility, and design end-to-end ML/AI solutions. You will then implement and deploy these solutions in production, working closely with data engineers, developers and business stakeholders.
This is a consulting role: you will both advise on the approach and work on the hands-on engineering yourself.
What you will do
Lead AI/ML discovery and solution design
Run discussions and workshops with clients to identify and evaluate AI/ML use cases with a clear business value lens.
Assess feasibility, required data, technical constraints and risks.
Propose end-to-end solution designs (e.g. LLM applications, predictive models, recommendation systems, optimisation setups).
Design and build ML/AI systems
Implement models using Python and modern ML frameworks (e.g. PyTorch, TensorFlow, JAX or similar).
Build robust training, evaluation and inference pipelines.
Work with both classical ML and modern deep learning, depending on the problem.
Work with GenAI and LLM-based solutions
Design and implement solutions using LLMs.
Build RAG-style systems with vector databases and orchestration frameworks.
Evaluate LLM-based solutions rigorously instead of relying on hype.
Productionise and operate ML/AI in the cloud
Deploy production-grade ML/AI systems on cloud platforms (AWS, Azure or GCP).
Implement MLOps practices: experiment tracking, model registry, CI/CD for ML, monitoring and retraining.
Use tools such as MLflow, Vertex AI, SageMaker, Azure ML, Docker and Kubernetes where relevant.
Handle data for ML (together with data engineers)
Prepare and manage data used for models when needed (ETL/ELT, feature engineering, basic data pipelines).
Collaborate closely with data engineers on data models and data platform choices, but remain able to do pragmatic data work yourself when required.
Guide clients on responsible, value-driven AI
Help them understand where AI adds real value, and where simpler solutions are better.
Translate business requirements into technical delivery plans and explain technical trade-offs clearly.
Advise clients on responsible AI, governance, model monitoring and reliability.
Support sales and act as an AI advocate
Join early client conversations to shape AI initiatives and proposals.
Help scope work, estimate effort and demonstrate solutions.
Advocate for practical, outcome-focused AI adoption, not “AI for the sake of AI”.
What you bring
Technical skills
You do not need every item below, but you should be confident in several and willing to grow into the rest.
Strong ML/AI engineering background
Solid experience deploying ML/AI systems into production.
Deep skills in Python and modern ML frameworks (PyTorch, TensorFlow, JAX or similar).
Experience with end-to-end ML pipelines from data to inference.
GenAI / LLM experience
Hands-on work with LLMs (OpenAI, Anthropic, Gemini, open-source models, etc.).
Experience with vector databases, RAG architectures and LLM application frameworks.
Understanding of LLM evaluation, prompting and basic LLMOps principles.
Software engineering practices
Strong programming habits: version control (Git), testing, code structure, reviews.
Experience with containerisation (Docker) and preferably some exposure to Kubernetes.
Comfortable using AI coding assistants (e.g. Copilot, Cursor, Claude Code, Gemini Code) in a deliberate way.
MLOps and cloud
Experience with one or more cloud ML platforms: SageMaker, Vertex AI, Azure ML or similar.
Familiarity with MLflow, Kubeflow or other MLOps tooling is a plus.
Understanding of model monitoring, drift detection and lifecycle management.
Data-related skills
Ability to work with typical data engineering tools and patterns (ETL/ELT, batch vs. real-time, dbt, Airflow or similar) at least at a practical level.
You do not need to be a pure data engineer, but you should understand how data platforms are built and operated.
Relevant cloud/ML certifications (e.g. AWS ML Specialty, GCP ML, Azure AI, Databricks ML) are beneficial but not required.
Consulting skills and mindset
Comfortable speaking with CxO-level and business stakeholders, not only technical teams.
Experience leading or co-leading workshops, requirements discussions and solution scoping.
Ability to translate ambiguous business problems into realistic ML/AI solutions and delivery plans.
Willing to be hands-on in implementation; this is not a research-only or slide-only role.
Calm and proactive in ambiguous consulting environments with shifting requirements.
Collaborative, straightforward and able to work in a small, evolving company setting.
Why this role might be interesting for you
You get to influence how AI is used in multiple organisations, not just one internal product.
You own a large part of the lifecycle: from use case discovery and design to production deployment and operations.
You work with the full scope of AI: LLMs, applied ML, optimisation and other methods – always tied to real business outcomes.
You have strong influence over models, tools, MLOps stack and architectures, as long as they support the client’s goals.
You help clients move away from hype towards practical, value-driven AI.
Practicalities
Location:
 You must be based in Finland and 
have a valid work permit in Finland.
Office presence:
 Ability to visit our Helsinki office roughly once a week (sometimes more depending on client and project needs).
How to apply
If this sounds like you, send us your CV and we’re happy to tell you more! We review applications continuously.

### Open Application

- **Location:** Helsinki, Finland
- **Work model:** Hybrid
- **Employment type:** Full-time
- **Apply:** https://jobs.gem.com/renessai-com/am9icG9zdDoMObO9K33KYHurt8zcUnBG

Come join us at Renessai!
We are interested in people who can help our clients use AI and data in a meaningful way – whether your strength is strategy, data engineering, ML/AI engineering, or something in between.
If you do not fit neatly into any of our open roles, but you have solid experience in this area and like working close to real business problems, we would still love to hear from you. We will shape the role around your skills and interests rather than force a fixed title.
What you could work on
Depending on your background, you might:
Shape AI and data strategies, roadmaps and operating models with business stakeholders.
Design and build modern data platforms and pipelines in the cloud.
Implement and productionise ML/AI and LLM-based solutions.
Act as a bridge between business and technical teams in complex organisations.
Help clients rethink processes, roles and ways of working as AI capabilities grow.
Who we are looking for
You might come from, for example:
Strategy / digital / data consulting.
Data, ML/AI or software engineering with strong interest in AI and data.
Product or business ownership for data/AI-driven services.
Leadership roles in data, analytics, AI or digital in a larger organisation.
We value:
Ability to work with both business and technical people.
Clear, honest communication.
Willingness to stay hands-on (workshops, analysis, design, implementation).
Comfort with ambiguity and changing situations.
Practicalities
You must be based in Finland and 
have a valid work permit in Finland.
Ability to visit our Helsinki office roughly once a week (sometimes more depending on client needs).
How to apply
Send us:
Your CV and as optional a cover letter. 
We review open applications continuously and will get in touch.

### AI Software Engineer

- **Location:** Helsinki, Finland
- **Work model:** Hybrid
- **Employment type:** Full-time
- **Team:** Agentic AI
- **Apply:** https://jobs.gem.com/renessai-com/am9icG9zdDr9hBINgh3TT6hO-RNan-3i

About the role
We're now looking for an AI SW Engineer to focus on Agentic AI 
to build the agentic layer of the systems we ship
. At Renessai 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.
Why Renessai
You'll be at the frontier of AI-native software, building real systems for real clients where agents are the core, not an afterthought. You'll own the work end-to-end and work in a team that develops with agents as the default way of working. Small company, fast decisions, serious impact.
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.
What you will do
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.
What you bring
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.
Practicalities
Location: You must be based in Finland and have a valid work permit in Finland.
Language: Fluent English. Finnish is considered a plus. 
Office presence: This is a hybrid role. We expect you to, if necessary due to client work, have the possibility to come to the office or client site. Client site presence is subject to project and client needs. Other than that we are flexible and open to discussion of the cadence of physical presence at the office. 
Salary: We operate in set ranges per seniority level, these ranges will be shared with you early on in the hiring process.
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.

All roles — and an open application if none fit: https://jobs.gem.com/renessai-com