AI Platform Engineer
dotLinkers
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Benefits offered by this job
Job summary
dotLinkers is seeking an AI Platform Engineer to own the infrastructure supporting AI-powered products. You will deliver end-to-end platform capabilities, including LLM gateways, retrieval systems, agent workflows, and security guardrails.
You will focus on reliability, observability, scalability, and cost efficiency, working across Engineering, Security, Infrastructure, and SRE teams to drive adoption and ensure production readiness.
Qualifications
- Must have practical experience building or operating production AI systems such as retrieval platforms or agent frameworks.
- Strong fundamentals in distributed systems and reliability.
- Knowledge of secure multi-tenant architectures and least-privilege access.
- Experience with observability, monitoring, and defining operational targets like SLOs.
- Ability to troubleshoot production issues and drive continuous improvement.
Responsibilities
- Own AI platform deliverables from problem definition through production launch and adoption.
- Design, build, and maintain platform capabilities like LLM gateways, retrieval systems, and developer tooling.
- Define measurable success criteria and SLOs using production metrics.
- Build reliable, observable, and secure systems with proper incident management.
- Develop interfaces, docs, and migration paths to enable easy platform adoption.
- Collaborate with Engineering, Product, Security, and Infra teams to align roadmaps.
Skills
Tools
Job description
Position: AI Platform Engineer
Employment: contract of employment up to 25 800 PLN gross/month
Working mode: remote
Our client is a global technology company providing software solutions for the fitness industry. Its products help fitness clubs, gyms, and studios manage their operations, memberships, payments, and customer engagement. The company is expanding its AI capabilities to bring intelligent automation and AI-powered experiences into its products and internal workflows. Its engineering teams are building a shared AI platform that enables developers to deliver AI-powered features faster, more securely, and more reliably.
We are looking for an AI Platform Engineer to help build and operate the infrastructure that supports AI-powered products across the organization. You will own platform capabilities end to end, from defining the problem and designing the solution to launching it in production, monitoring its performance, and driving adoption across engineering teams. Your work will involve building and improving LLM gateways, retrieval systems, agent platforms, evaluation frameworks, developer tools, and security guardrails. You will focus on reliability, observability, scalability, and cost efficiency while ensuring that other engineers can easily integrate and use the platform. This is a hands-on engineering role focused on production systems rather than model training or AI research.
Own AI platform deliverables from initial problem definition through implementation, production launch, adoption, and ongoing improvement.
Design, build, and maintain platform capabilities such as LLM gateways, retrieval systems, agent workflows, evaluation frameworks, and developer tooling.
Define measurable success criteria and service-level objectives (SLOs), using production metrics to guide improvements.
Build reliable, observable, and resilient systems with predictable failure handling and effective incident management.
Develop clean interfaces, documentation, reference implementations, and migration paths to make platform adoption straightforward.
Design secure AI execution environments with appropriate permissions, tenant isolation, auditability, and access controls.
Apply distributed systems principles, including consistency, idempotency, concurrency management, and resilience.
Participate in on-call rotations, respond to production incidents, and implement improvements based on post-incident reviews.
Collaborate with Engineering, Product, Security, Infrastructure, SRE, and Developer Experience teams.
Establish reusable technical standards and best practices for building and operating production-ready AI systems.
Use AI coding tools and coding agents effectively, ensuring their output meets engineering and quality standards.
Practical experience building or operating production AI systems, such as retrieval platforms, LLM applications, agent systems, or AI developer tools.
Strong software engineering fundamentals and experience designing and operating distributed systems.
Understanding of reliability, concurrency, idempotency, consistency, failure modes, and secure multi-tenant architectures.
Knowledge of AI system evaluation, retrieval quality, agent reliability, and the trade-offs between quality, latency, and cost.
Experience with observability, monitoring, measurable success criteria, and operational targets such as SLOs.
Understanding of secure AI execution, including least-privilege access, permission management, auditability, and policy enforcement.
Experience taking a technical solution from initial concept to production and remaining accountable for its performance and adoption.
Ability to troubleshoot production issues, participate in incident response, and drive continuous improvement.
Experience using AI coding tools while independently reviewing and validating generated code.
Strong communication and collaboration skills, with the ability to explain complex technical concepts to different stakeholders.
A customer-focused mindset and an interest in building reusable capabilities that help other engineering teams work more efficiently.
Experience with LLM gateways, RAG, agent frameworks, AI evaluation systems, or internal AI platforms.
Familiarity with OpenTelemetry, distributed tracing, and AI observability.
Experience with FinOps, AI cost optimization, or usage-based cost monitoring.
Knowledge of application security, identity and access management, and policy enforcement.
Experience with search, ranking, relevance evaluation, or experimentation.
Background in internal developer platforms, multi-tenant infrastructure, SDKs, or developer enablement.
Familiarity with API gateways, routing systems, service orchestration, and workflow engines.
Open PTO policy for eligible employees.
Quarterly company-wide Days of Disconnect.
Parental leave and pet-related leave.
Quarterly fitness reimbursement.
Medical, dental, and vision coverage.
Employee Assistance Program (EAP).
Calm App subscription for the employee and eligible dependents.
Contract of employment up to 310 000 PLN gross/year
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