Forward Deployed Engineer

About us

OMNIVISER is building an AI-powered Business Operating System that connects all company data to deliver real-time insights, profit projections, and clear decisions. We help leaders cut through data overload and act faster with proactive, context-aware AI that drives measurable business outcomes.

We are currently transitioning from a startup to a scale-up - developing our product, scaling our organization, and preparing for international expansion.

About the role

We are looking for a Forward Deployed Engineer who will work where our product meets the reality of a specific customer. You will start by understanding how the company actually operates, and only then decide what needs to be built.

You will take ownership of a project from the first conversation with management to a working production solution. You will work directly with customer data and systems, adapt our product to their environment, and remain responsible for the result - including whether people actually start using it.

Every implementation is also product discovery. You will be among the first to see what the product cannot yet do, decide what should remain custom and what can be generalized, and bring those insights back into the product roadmap.

Responsibilities

• Enter projects early, before the exact solution is known, run technical workshops, talk with management about real problems, validate feasibility, and translate them into architecture
• Define success metrics and the value to be delivered at each stage of an implementation
• Build the solution yourself: agents, RAG systems, orchestration, and production code in Python and SQL, from rapid prototype to production
• Integrate our product with customer APIs, data silos, and legacy systems inside their security constraints
• Work with imperfect environments and organize fragmented data when there is no dedicated data team on the customer side
• Build evals, baselines, quality gates, and monitoring that remain operational after the implementation is handed over
• Design systems customers can rely on, including retries and model fallbacks, cost limits, human-in-the-loop for irreversible actions, prompt-injection resistance, and strict data boundaries
• Drive adoption and measure it, making sure people actually use the solution and that the implementation produces visible results
• Turn recurring implementation patterns into reusable modules, accelerators, and ready-made solutions that shorten future deployments
• Bring product gaps and customer needs back to Product and Ops so implementation insights directly influence the roadmap
• Support sales in meetings with new customers by demonstrating the product, designing the first use case, and defining how success will be measured
• Work with tools such as Claude Code or Cursor while remaining accountable for the quality of the code that reaches the customer

Requirements

• 4-6 years of experience in software engineering, including LLM-based solutions shipped to production rather than left at prototype stage
• Very strong Python and SQL skills, production APIs, and integrations with systems customers already use
• Strong knowledge of agent architectures: tool calling, context engineering, sub-agents, state management, and orchestration, including MCP servers or custom tool-calling interfaces
• Ability to choose an agent architecture based on the task and its expected failure modes
• Production experience with retrieval: vector databases, embeddings, hybrid search, re-ranking, chunking, and context management
• Experience with data modeling, ETL/ELT pipelines, performance tuning, and unstructured data
• Experience with evaluation systems for generative solutions, from baselines and regression tests to LLM-as-a-judge, plus tracing and observability in Langfuse or LangSmith
• Experience deploying and maintaining cloud systems, especially Azure, with containerization and CI/CD
• Understanding of application security: OWASP, secrets management, input validation, permissions, personal data, and attacks specific to LLM applications
• Experience leading customer implementations from discovery to production and communicating technical trade-offs to non-technical decision-makers
• Comfort working in immature environments with spreadsheet-based data, limited documentation, and no dedicated data team
• Strong judgement when narrowing scope, setting priorities, and balancing speed, quality, and scope
• Ability to define implementation success metrics and demonstrate business value in the customer’s own numbers
• Daily use of agentic engineering tools and the ability to review and productionize model-generated code
• Very good communication skills in Polish and English

Nice to have

• Experience building this type of function in a company from scratch
• Experience in a similar role in a product company
• Knowledge of the systems mid-sized companies actually run on, including ERP, CRM, accounting systems, and spreadsheet-heavy workflows
• Ability to quickly build a simple interface to demonstrate an idea instead of only describing it
• Experience handing a solution over to a customer team so they can continue developing it independently
• Experience in presales, technical demos, and proof-of-value design
• Experience expanding a customer relationship from the first implementation into additional areas

Who we are looking for

• Someone with high agency who can take a project from an ambiguous starting point to a working production solution
• A customer- and outcome-oriented engineer who makes decisions based on real needs and measurable business impact
• Someone who combines technical rigor with pragmatism and can make good trade-offs under uncertainty
• A strong communicator who can talk technically with customer engineers and clearly with business stakeholders, in Polish and English
• An AI-native engineer who uses generative AI in everyday work and keeps up with the evolving tool ecosystem
• Someone who follows through on commitments, keeps track of open topics, and communicates early when delivery is at risk

What we offer

• End-to-end ownership of customer implementations, from discovery and architecture to production and adoption
• Direct work with customers, including management, technical teams, and real production environments
• A hands-on role combining engineering, product discovery, and business problem solving
• Real influence on the product roadmap through insights gathered during implementations
• The opportunity to turn customer-specific solutions into reusable modules and accelerators
• An AI-native, fast-moving environment with a strong focus on ownership, measurable outcomes, and continuous exploration
• Compensation: 23 000 - 30 000 PLN net/month + VAT (B2B)