Edgerunners
Careers at Edgerunners

Engineering with Purpose

At Edgerunners, we build AI-powered software and intelligent systems that solve complex, real-world business problems.

  • Enterprise AI
  • Autonomous agents
  • Industrial intelligence
  • Data engineering
  • Scalable software platforms

We are looking for engineers who combine strong technical fundamentals with curiosity, ownership, and the ability to turn ambiguous challenges into reliable, production-ready solutions.

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Open positions
10
Location
Relocation opportunities available
Relocation package
Available for successful candidates, subject to role, destination, and individual arrangements
Work environment
Collaborative, engineering-driven, AI-native

We value demonstrated ability, thoughtful engineering, continuous learning, and measurable impact over credentials or familiarity with a particular technology alone.

Open positions

Ten ways to build what's next.

Open a role to read its responsibilities and qualifications.

Applied AI · Customer delivery · Architecture · Quality · Platform · Data & knowledge · Industrial · Product · Security

  1. Senior Applied AI EngineerApplied AILLM applications · RAG · Evaluation

    You will design and implement AI-powered capabilities that integrate language models, enterprise data, and business applications. Your focus will be turning AI prototypes into dependable software that delivers measurable value.

    Responsibilities

    • Design and develop production-grade LLM applications.
    • Implement retrieval-augmented generation (RAG), structured outputs, and tool calling.
    • Integrate AI capabilities with APIs, databases, and existing enterprise systems.
    • Build document processing, information extraction, and intelligent automation pipelines.
    • Evaluate model performance, improve accuracy, and reduce hallucinations.
    • Optimize latency, inference costs, and application reliability.
    • Collaborate with product and engineering teams to translate business requirements into technical solutions.

    Required qualifications

    • Strong programming skills in Python or TypeScript.
    • Practical experience building applications with LLM APIs or open-weight models.
    • Understanding of embeddings, vector search, RAG, prompt design, and structured generation.
    • Experience integrating AI systems with databases, APIs, and backend services.
    • Familiarity with automated testing, evaluation datasets, and production monitoring.
    • Ability to reason about security, reliability, and data privacy in AI applications.

    Preferred qualifications

    • Experience with LangGraph, LlamaIndex, or comparable orchestration frameworks.
    • Familiarity with model serving, quantization, and inference optimization.
    • Experience with enterprise knowledge systems and access-controlled retrieval.
    • Experience deploying AI applications in private or on-premise environments.
    Apply for this role
  2. AI Agent EngineerApplied AITool-using agents · Workflows · Human-in-the-loop

    You will build intelligent agents capable of using tools, interacting with enterprise systems, coordinating tasks, and executing multi-step workflows under appropriate control.

    Responsibilities

    • Design agent architectures, tool interfaces, and execution workflows.
    • Implement task planning, state management, memory, and context selection.
    • Build integrations with internal APIs, databases, document repositories, and external services.
    • Implement human approval, permission boundaries, retries, and recovery mechanisms.
    • Evaluate agent task completion, tool selection, and execution quality.
    • Build traceable and observable agent execution pipelines.
    • Identify when deterministic software is preferable to autonomous model-driven behavior.

    Required qualifications

    • Strong Python or TypeScript programming skills.
    • Experience building tool-using LLM applications or multi-step AI workflows.
    • Understanding of API integration, asynchronous execution, state management, and error handling.
    • Familiarity with structured outputs, context windows, retrieval, and model limitations.
    • Ability to implement robust tests for non-deterministic systems.
    • Strong understanding of secure tool execution and human-in-the-loop controls.

    Preferred qualifications

    • Experience with LangGraph, Semantic Kernel, or similar agent frameworks.
    • Experience designing multi-agent systems or workflow orchestration platforms.
    • Familiarity with Model Context Protocol (MCP).
    • Experience integrating agents with enterprise identity, authorization, and audit systems.
    Apply for this role
  3. Forward Deployed Engineer (FDE)Customer deliveryCustomer environments · Integrations · Solution design

    You will work closely with customers to understand complex operational challenges and implement software solutions directly within their business environments.

    This role combines software engineering, solution architecture, technical consulting, and hands-on delivery.

    Responsibilities

    • Discover customer requirements and translate them into technical specifications.
    • Develop prototypes and production integrations for customer-specific use cases.
    • Connect applications to existing databases, APIs, and enterprise systems.
    • Deploy, test, and troubleshoot solutions in customer environments.
    • Collaborate with stakeholders to validate outcomes and prioritize improvements.
    • Identify reusable components that can become part of Edgerunners' core products.
    • Communicate technical trade-offs and implementation progress clearly.

    Required qualifications

    • Strong software engineering skills in Python, TypeScript, or another relevant language.
    • Experience building and integrating production applications.
    • Understanding of APIs, databases, authentication, networking, and deployment.
    • Ability to investigate unfamiliar systems and resolve complex technical problems.
    • Strong written and verbal communication skills.
    • Comfort working with incomplete requirements and changing priorities.
    • Willingness to collaborate directly with customers and technical stakeholders.

    Preferred qualifications

    • Experience with enterprise software, AI integration, or digital transformation.
    • Familiarity with Kubernetes, Docker, CI/CD, and observability.
    • Experience in industrial, financial, governmental, or other complex enterprise environments.
    • Experience translating business processes into software workflows.
    Apply for this role
  4. AI Systems EngineerArchitectureSystem design · Multi-tenancy · Observability

    You will design the architecture surrounding AI capabilities, ensuring that models, data, tools, application services, and security controls operate as a coherent system.

    Responsibilities

    • Design end-to-end architectures for AI-enabled applications.
    • Define service boundaries, APIs, data models, and integration patterns.
    • Architect context management, retrieval, memory, and workflow execution.
    • Design authentication, authorization, and tenant isolation.
    • Establish system observability, failure handling, and recovery strategies.
    • Evaluate architectural trade-offs involving model selection, latency, cost, and reliability.
    • Create reusable architectural patterns for enterprise AI products.

    Required qualifications

    • Strong software architecture and system design fundamentals.
    • Experience with backend services, APIs, databases, and distributed systems.
    • Proficiency in Python, TypeScript, or comparable production languages.
    • Understanding of LLM application architectures and integration patterns.
    • Familiarity with security, testing, observability, and deployment practices.
    • Ability to document technical decisions and explain architectural trade-offs.

    Preferred qualifications

    • Experience with event-driven architectures, queues, and workflow engines.
    • Familiarity with Kubernetes and service-oriented architectures.
    • Experience designing multi-tenant enterprise applications.
    • Experience with private AI deployments and data governance.
    Apply for this role
  5. AI Evaluation & Reliability EngineerQualityEvaluation datasets · Regression testing · Monitoring

    You will ensure that AI-powered products behave consistently, satisfy business requirements, and remain reliable as models, prompts, data, and application logic evolve.

    Responsibilities

    • Develop evaluation datasets based on real business tasks.
    • Build automated tests for model outputs, tool calls, and complete workflows.
    • Measure accuracy, task completion, hallucination rates, latency, and cost.
    • Implement regression testing for prompts, models, and agent behavior.
    • Analyze failures and identify their underlying causes.
    • Establish quality thresholds and release criteria for AI features.
    • Develop monitoring and reporting for production AI performance.

    Required qualifications

    • Strong programming skills in Python or TypeScript.
    • Experience with automated testing, data analysis, or machine learning evaluation.
    • Ability to design representative test cases and measurable acceptance criteria.
    • Understanding of LLM limitations, nondeterminism, and evaluation challenges.
    • Familiarity with APIs, data processing, and CI/CD.
    • Strong analytical thinking and attention to detail.

    Preferred qualifications

    • Experience with LLM evaluation frameworks and model benchmarking.
    • Familiarity with observability, distributed tracing, and production monitoring.
    • Experience in regulated or accuracy-sensitive applications.
    • Knowledge of statistical evaluation and experimental design.
    Apply for this role
  6. AI Infrastructure & Inference EngineerPlatformModel serving · GPU workloads · Kubernetes

    You will build and maintain the infrastructure required to run AI applications and models efficiently, reliably, and securely, including private and on-premise deployments.

    Responsibilities

    • Deploy and operate model inference services.
    • Optimize GPU utilization, throughput, latency, and resource consumption.
    • Implement containerized deployment and automated release pipelines.
    • Manage model versions, configuration, secrets, and service dependencies.
    • Establish monitoring, logging, alerting, and incident response practices.
    • Improve deployment repeatability across development, testing, and production environments.
    • Support secure, scalable AI infrastructure for enterprise customers.

    Required qualifications

    • Strong Linux and networking fundamentals.
    • Experience with Docker and container orchestration.
    • Practical experience with Kubernetes or comparable infrastructure platforms.
    • Understanding of CI/CD, observability, service reliability, and infrastructure automation.
    • Familiarity with Python scripting and API-based services.
    • Ability to troubleshoot performance, connectivity, and deployment issues.

    Preferred qualifications

    • Experience operating LLM inference engines or GPU workloads.
    • Familiarity with vLLM, NVIDIA Triton, or comparable inference systems.
    • Experience with model quantization, batching, and caching.
    • Familiarity with Prometheus, Grafana, OpenTelemetry, and distributed tracing.
    • Experience with private cloud, bare-metal, or on-premise deployments.
    Apply for this role
  7. Context & Knowledge Systems EngineerData & knowledgeRetrieval · Knowledge graphs · Access control

    You will build the data and knowledge foundations that allow AI systems to retrieve relevant information, understand organizational context, and provide traceable, permission-aware answers.

    Responsibilities

    • Design enterprise document ingestion and processing pipelines.
    • Build retrieval systems using metadata, embeddings, and hybrid search.
    • Implement document chunking, indexing, deduplication, and data quality controls.
    • Develop knowledge graphs or structured knowledge representations when appropriate.
    • Preserve source attribution and traceability for AI-generated responses.
    • Implement access-controlled retrieval and tenant-specific data boundaries.
    • Evaluate retrieval quality and improve context selection.

    Required qualifications

    • Strong programming skills in Python or TypeScript.
    • Experience with databases, data processing, and API integration.
    • Understanding of information retrieval, embeddings, and vector search.
    • Familiarity with document processing and data modeling.
    • Ability to design data quality and retrieval evaluation workflows.
    • Understanding of permissions and privacy in enterprise information systems.

    Preferred qualifications

    • Experience with Qdrant, Elasticsearch, OpenSearch, or comparable technologies.
    • Familiarity with PostgreSQL, MongoDB, and knowledge graph systems.
    • Experience with OCR, document parsing, and multilingual content.
    • Familiarity with MCP and enterprise knowledge integrations.
    Apply for this role
  8. Industrial AI EngineerIndustrialPredictive maintenance · Time series · Anomaly detection

    You will develop data-driven solutions for industrial environments, including predictive maintenance, anomaly detection, operational analytics, and decision support.

    Responsibilities

    • Analyze industrial, equipment, maintenance, and production data.
    • Develop anomaly detection and predictive modeling pipelines.
    • Identify operational patterns, leading indicators, and potential failure conditions.
    • Build dashboards, alerts, and decision-support capabilities.
    • Integrate with existing industrial information systems using approved interfaces.
    • Collaborate with domain experts to validate models and operational recommendations.
    • Measure performance against operational metrics and business outcomes.

    Required qualifications

    • Strong Python and data analysis skills.
    • Experience with time-series data, statistics, or machine learning.
    • Understanding of data quality, feature engineering, and model validation.
    • Familiarity with SQL, data pipelines, and visualization.
    • Ability to translate operational problems into measurable analytical tasks.
    • Strong communication skills for working with domain experts.

    Preferred qualifications

    • Experience with mining, manufacturing, energy, or process industries.
    • Familiarity with SCADA, historians, OPC UA, or industrial data platforms.
    • Knowledge of predictive maintenance and anomaly detection.
    • Experience with edge computing and industrial cybersecurity.
    • Understanding of the distinction between IT and operational technology (OT).
    Apply for this role
  9. AI-Native Product EngineerProductTypeScript · Next.js · AI coding agents

    You will design, build, and ship complete software features using modern engineering practices and AI-assisted development tools. You will own outcomes across the frontend, backend, data layer, testing, and deployment.

    Responsibilities

    • Build responsive web applications and production APIs.
    • Implement product features from user requirements through deployment.
    • Integrate AI capabilities into application workflows.
    • Design maintainable components, data models, and service interfaces.
    • Use AI coding agents to accelerate implementation, debugging, testing, and refactoring.
    • Review generated code and ensure correctness, security, and maintainability.
    • Collaborate with design and product stakeholders to deliver high-quality user experiences.

    Required qualifications

    • Strong experience with TypeScript and modern JavaScript.
    • Experience with React and Next.js or comparable frameworks.
    • Understanding of backend development, APIs, databases, and authentication.
    • Familiarity with automated testing, version control, and CI/CD.
    • Ability to use AI coding tools effectively while maintaining engineering quality.
    • Strong problem-solving skills and a focus on shipping working software.

    Preferred qualifications

    • Experience with Node.js, NestJS, Express, or comparable backend frameworks.
    • Familiarity with PostgreSQL, MongoDB, and data modeling.
    • Experience with Tailwind CSS, component libraries, and accessible UI design.
    • Familiarity with AI APIs, agent frameworks, and structured generation.
    • Experience deploying and operating production applications.
    Apply for this role
  10. AI Security EngineerSecurityThreat modeling · Prompt injection · Permission boundaries

    You will help secure AI-powered applications, agents, and enterprise data integrations against unauthorized access, data exposure, and unsafe execution.

    Responsibilities

    • Assess security risks in LLM applications and autonomous agents.
    • Design permission boundaries for tools, APIs, and data retrieval.
    • Implement controls against prompt injection and sensitive-data leakage.
    • Review authentication, authorization, secrets management, and audit trails.
    • Conduct security testing and threat modeling.
    • Establish safe execution patterns for AI-driven actions.
    • Collaborate with engineering teams to incorporate security throughout development.

    Required qualifications

    • Strong software engineering or application security background.
    • Understanding of authentication, authorization, and API security.
    • Experience with security testing, threat modeling, or secure software development.
    • Familiarity with common LLM application risks.
    • Ability to implement practical controls and verify their effectiveness.
    • Strong analytical and documentation skills.

    Preferred qualifications

    • Experience with OWASP guidance for LLM applications.
    • Familiarity with identity providers, OIDC, OAuth 2.0, and secrets management.
    • Experience with Kubernetes security and infrastructure hardening.
    • Knowledge of data loss prevention, auditability, and enterprise security requirements.
    Apply for this role

What we expect from every engineer

Regardless of position, we value people who demonstrate:

  • Ownership

    Take responsibility for outcomes, not just assigned tasks.

  • Engineering judgment

    Understand trade-offs instead of following trends blindly.

  • AI-native execution

    Use AI tools productively while verifying their output.

  • Continuous learning

    Stay curious and adapt to rapidly changing technologies.

  • Communication

    Explain complex problems clearly and collaborate effectively.

  • Pragmatism

    Prefer measurable customer value over unnecessary complexity.

  • Reliability

    Build systems that can be tested, monitored, maintained, and improved.

  • Integrity

    Handle customer data, credentials, and production systems responsibly.

Candidates are evaluated on demonstrated skills, relevant experience, technical reasoning, and their ability to learn. We welcome strong candidates from different educational and professional backgrounds.

What Edgerunners offers

Meaningful problems, real ownership, and room to grow.

Relocation support

We welcome qualified candidates who are interested in relocating to join our team.

Depending on the position, destination, and individual circumstances, our relocation package can be discussed during the recruitment process and may include agreed support for relocation logistics and the transition to a new location.

Any immigration, visa, travel, or accommodation support will be clarified individually rather than assumed to be included in every offer.

Non-financial benefits

  • Engineering Autonomy

    Work on meaningful technical problems and contribute to architectural decisions, implementation strategies, and engineering standards.

  • AI-Native Working Environment

    Use modern AI development tools and workflows to improve productivity, experimentation, and software delivery.

  • End-to-End Product Ownership

    Contribute across discovery, architecture, implementation, deployment, and continuous improvement instead of being restricted to a narrow part of the development process.

  • Continuous Learning

    Develop expertise in emerging AI technologies, agent architectures, enterprise systems, and modern software engineering practices through practical work.

  • Direct Technical Impact

    Work on solutions that address real business and operational challenges.

Apply

Show us what you've built.

Pick a role — or send an open application — and tell us about work you're proud of.

What we look at

  • Demonstrated skills
  • Relevant experience
  • Technical reasoning
  • Ability to learn
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