We're building the operating system for modern enterprises.

01 · Customer delivery and deployment

• Lead end-to-end Compass deployments at enterprise customers, from initial discovery through go-live, adoption and solution expansion.
• Quickly understand customer processes, organization, systems and information assets.
• Identify and prioritize use cases with the highest operational and economic impact.
• Configure Compass based on the customer's domain, working on ontology models, Context Graph, workflows, AI agents, skills and operational outputs.
• Build prototypes and first working solutions rapidly, aiming to prove value in weeks rather than quarters.
• Support users and stakeholders in platform adoption.
• Ensure quality, security, reliability and traceability of solutions, even in regulated environments or with sensitive data.

02 · Process analysis and transformation

• Translate complex and often unstructured business problems into functional and technical requirements.
• Redesign decision and operational processes leveraging Compass capabilities in context organization, analysis and automation.
• Run interviews, workshops and process mapping sessions with stakeholders from different functions.
• Define KPIs, adoption metrics and business cases for deployments.
• Quantify and communicate solution impact to executive sponsors.
• Turn customer-specific needs into replicable models for other projects and industries.

03 · Customer management

• Be the main technical and strategic point of reference for the customer during the engagement.
• Manage expectations, priorities, dependencies and stakeholders at different levels of the organization.
• Present analysis, results and roadmaps to executive audiences with clarity, synthesis and rigor.
• Build trusted relationships with IT teams, business functions and management.
• Identify expansion opportunities into new use cases, business functions or organizational units.
• Support the commercial team in pre-sales, solution design and scoping activities.
• Navigate effectively inside complex organizations and politically sensitive contexts.

04 · Software and data integration

• Design integrations between Compass and customer systems, including CRM, ERP, data warehouses, proprietary applications, internal APIs and external data sources.
• Define requirements for data acquisition, transformation and normalization.
• Work with heterogeneous, incomplete, unstructured or poorly documented data.
• Contribute to defining data models and ontologies consistent with customer processes and language.
• Coordinate with customer technical teams and the MarketLabs product team to ensure correct solution implementation.
• Collaborate with product and engineering to turn patterns from deployments into native platform components.
• Use AI-assisted development and prototyping tools at an advanced level.

Must have

• At least 4 years of overall professional experience.
• At least 2 years of experience in strategy, management or technology consulting, preferably at McKinsey, BCG, Bain or comparable firms, or in forward deployment, solution engineering or enterprise implementation roles.
• Direct experience managing enterprise customers and complex projects with multiple stakeholders.
• Ability to interact authoritatively with both C-level executives and technical or operational teams.
• Strong ability to structure ambiguous problems, formulate hypotheses and quickly turn them into verifiable solutions.
• Concrete knowledge of core business processes such as sales, operations, procurement, risk, compliance or strategic planning.
• Good understanding of software and data integrations, including APIs, data pipelines, SQL and information modeling.
• Ability to engage effectively with development, data engineering, IT and cybersecurity teams.
• Excellent written and oral communication skills in Italian and English.
• Autonomy, accountability and strong result orientation.
• Ability to work effectively in a startup environment characterized by speed, ambiguity and distributed ownership.
• Willingness to travel to customer sites, approximately 30-40% of the time.

Nice to have

• Direct experience as Forward Deployed Engineer, Forward Deployed Software Engineer or Solution Engineer in companies with a similar delivery model.
• Experience implementing enterprise platforms such as Palantir Foundry, Celonis, C3 AI, Dataiku or equivalent solutions.
• Experience in defense, security, financial services, public administration, energy or critical infrastructure sectors.
• Familiarity with Large Language Models, AI agents, RAG systems, knowledge graphs and enterprise Generative AI applications.
• Knowledge of software architectures, data engineering or enterprise application development.
• Quantitative background in engineering, computer science, mathematics, physics, data science or quantitative economics.
• MBA or previous experience in strategy consulting firms.
• Experience in B2B enterprise startups or scale-ups.

01 · Full Stack and product engineering

• Design and develop complex web applications with an end-to-end JavaScript/TypeScript stack, using Next.js, React, Node.js and REST or GraphQL APIs.
• Build performant, accessible interfaces to explore data, manage workflows, configure AI agents and turn complex outputs into simple operational experiences.
• Develop robust backend services with modern patterns, including modular monoliths, microservices, serverless, event-driven architectures and job queues.
• Implement authentication, authorization, role management, audit trails and multi-tenant features suitable for enterprise contexts.
• Work with relational and non-relational databases, especially PostgreSQL and Redis, using ORMs such as Prisma or Drizzle.
• Write testable, maintainable code, caring about automated tests, code reviews, technical documentation and developer experience quality.
• Contribute to architectural choices and to the evolution of Compass's design system and shared components.

02 · AI agent development

• Design, develop and orchestrate AI agents using Vercel AI SDK, LangChain.js, equivalent frameworks or custom solutions.
• Integrate OpenAI, Anthropic and open-source models into real product workflows, keeping the architecture as provider-agnostic as possible.
• Build RAG pipelines with vector databases and technologies such as pgvector, Pinecone or Weaviate.
• Define prompts, structured outputs, function calling and tool use for autonomous and semi-autonomous agents.
• Implement state management, memory, planning, retry, human-in-the-loop approvals and execution traceability.
• Build evals, guardrails and observability systems to measure quality, reliability, latency and costs of AI features.
• Turn recurring AI capabilities into modular, configurable skills inside Compass.

03 · AI-assisted development and prototyping

• Use AI-assisted development tools at an advanced level, such as Cursor, Claude Code, Windsurf, v0, Bolt and equivalent solutions.
• Use AI tools to accelerate codebase analysis, prototyping, scaffolding, refactoring, test generation and documentation.
• Experiment with new AI-native development paradigms and integrate them into the daily workflow without compromising control, security and code quality.
• Contribute to defining internal best practices for context management, code review, testing and responsible use of generated code.
• Quickly evaluate new tools and frameworks, distinguishing genuinely useful technologies from short-term trends.

04 · Asynchronous backend, data and integrations

• Design asynchronous workflows and event-driven systems using Redis, BullMQ, webhooks and processing queues.
• Develop integrations with CRM, ERP, data warehouses, proprietary applications, internal APIs and external data sources.
• Build pipelines for acquisition, transformation, normalization and indexing of structured and unstructured data.
• Manage idempotency, concurrency, retry, rate limiting, resilience and consistency of distributed processes.
• Contribute to modeling the entities, relationships and workflows that feed Compass's ontology layer.

05 · DevOps, cloud and reliability

• Manage cloud infrastructure on Azure, AWS or equivalent platforms.
• Configure and maintain CI/CD pipelines with GitHub Actions or GitLab CI, automating tests, builds and deployments.
• Containerize applications with Docker and contribute to orchestration through Kubernetes or managed services when needed.
• Use Infrastructure as Code with Terraform, Pulumi, SST or equivalent tools.
• Implement monitoring, logging, tracing and alerting with tools such as Sentry, Grafana, Datadog or OpenTelemetry.
• Manage development, staging and production environments, secret management, migrations, backups and rollback strategies.
• Optimize performance, reliability and costs of infrastructure and AI model calls.

Must have

• At least 3 years of professional experience in Full Stack development with JavaScript and TypeScript.
• Concrete experience with Next.js, including App Router, React and Node.js in production environments.
• Strong mastery of TypeScript, asynchronous programming, API design and software architecture principles.
• Experience with PostgreSQL, Redis and at least one modern ORM such as Prisma or Drizzle.
• Practical experience integrating Large Language Models or developing AI features used by real users.
• Familiarity with at least one SDK or framework for AI agents and tool calling, such as Vercel AI SDK or LangChain.js.
• Knowledge of Git, CI/CD, Docker and at least one cloud platform.
• Ability to design, test, debug and monitor end-to-end applications.
• Advanced and thoughtful use of AI-assisted development tools.
• Attention to code quality, security, performance and maintainability.
• Autonomy, ownership and ability to work in a startup environment characterized by speed, ambiguity and distributed responsibility.
• Good written and oral communication skills in Italian and English.

Nice to have

• Experience with RAG pipelines, vector databases, evals and AI system observability.
• Experience developing multi-agent systems, stateful workflows or complex orchestrations.
• Deep knowledge of BullMQ, distributed queues, event sourcing or event-driven architectures.
• Experience with GraphQL, microservices, serverless or high-volume distributed systems.
• Knowledge of Terraform, Pulumi, Kubernetes or managed orchestration platforms.
• Experience with SSO, SAML, OIDC, RBAC, audit logs, multi-tenancy and enterprise security requirements.
• Familiarity with knowledge graphs, ontologies, graph databases or semantic modeling.
• Experience in B2B SaaS startups or scale-ups and in developing products for enterprise customers.
• Open-source contributions, personal projects or a technical portfolio demonstrating curiosity and execution ability.
• Background in computer science, engineering, mathematics or quantitative disciplines, or equivalent professional experience.