Position overview
We’re looking for an Applied AI Engineer to turn a client’s AI ambition into working systems — and to build it hands-on, right alongside them. You’ll help shape the approach early, build proofs of concept that prove out what’s possible in a matter of weeks, and ship production-grade AI not long after. It’s real engineering done in close partnership with the client: understanding the need, then writing the code that brings it to life. An applied role across the whole arc of an engagement — from scoping the right solution to delivering it in production.
About deepsense.ai
deepsense.ai is a 120-person AI/ML consultancy with Anthropic and OpenAI partner credentials. For over a decade we’ve delivered applied AI projects for companies like J&J, Sky, John Deere, and GLS — spanning LLM applications, agents, MLOps, and data science. We’re a people-first organization that believes in deep technical craft and real ownership. Our engineers don’t just advise; they build things that run in production.
About the role
The Applied AI Engineer works close to the client across the whole engagement: in the presales conversations understanding what they actually need, drafting the architecture for it, and then delivering it hands-on, super close with the client. You’ll move across that work fluidly — one moment shaping the approach in a scoping workshop, the next committing code to their repo and owning a production agent in their environment.
You’ll work alongside our own team and the client’s, and you’ll be equally at home in a discovery workshop and a pull request review.
Responsibilities
- Partner with Delivery Managers to scope and win AI engagements — run technical discovery, design solution architectures, build and demo POCs that help win the work
- Act as the primary technical advisor during early post-sales phases, shaping how clients build on top of LLMs and agentic systems
- Work hands-on inside client engagements — in their systems and close to their team — shipping production code and, where the engagement calls for it, owning critical AI deployments end to end
- Design and build LLM-powered applications: RAG pipelines, multi-agent systems, MCP integrations, evaluation frameworks, and production inference stacks
- Run technical workshops and architecture reviews; transfer knowledge in ways that build lasting capability in client teams
- Contribute to reusable internal assets: solution blueprints, reference implementations, prompt libraries, evaluation toolkits
- Stay at the leading edge of the applied AI space — new models, tooling, and patterns — and bring that knowledge into client work
You must have
- 4+ years of software engineering experience, with at least 2 years working on AI/ML or LLM-powered systems in production
- Hands-on production experience with LLMs: prompting, context engineering, agent architectures, tool use, RAG, evaluation
- Strong Python skills and experience shipping software that real users depend on
- Demonstrated ability to work directly with clients — you can run a technical scoping call, facilitate a workshop, and earn trust quickly with engineers and non-engineers alike
- Experience owning deliverables end-to-end in ambiguous environments without close supervision
- Familiarity with cloud platforms (GCP / AWS / Azure) and containerized deployment (Docker, Kubernetes)
You may have
- Experience supporting the sales process as the technical expert — building POCs, scoping, and answering clients’ technical questions before a deal is signed
- Hands-on experience with agentic frameworks: LangGraph, CrewAI, Pydantic AI, or MCP server development
- Familiarity with LLMOps tooling: LangSmith, Langfuse, W&B, or equivalent
- Experience building in regulated-industry environments (finance, healthcare, manufacturing)
- Exposure to model evaluation methodologies, or LLM-as-a-judge patterns
- A track record of building internal tools, demos, or reference implementations that other engineers reuse
We offer
- Work on frontier AI problems with real clients and real production stakes
- Close collaboration with Anthropic and OpenAI through our partnerships, working at the frontier of applied AI
- A team of 120+ specialists you can learn from and co-create with
- Competitive compensation benchmarked to the market
- Flexible hybrid work — remote + offices and coworks in major Polish cities
- Conference budget and learning allowance
- Equipment of your choice
Why join us
Applied AI is no longer a niche. Clients expect working systems, not slide decks. At deepsense.ai you’ll build things that matter, with people who’ve been doing this seriously for over a decade — and you’ll be doing it at a moment when the technology is moving faster than anyone can keep up with alone. If you want to be close to the frontier and ship real work, this is that role.
Benefits
- Flexible working hours and hybrid model (offices and coworks in major Polish cities)
- B2B contract
- Private medical care
- Sport subscription (Multisport)
- English lessons
- Mental health support
- Regular team meetups (at least a few times per year)