Senior Full-Stack Engineer
On-siteHellerup, Region Hovedstaden, Kingdom of Denmark
Job Summary
Design and implement full-stack applications from early concepts to scalable production systems, managing architecture decisions across frontend, backend, data, and cloud layers. Build high-quality services using TypeScript or Python while integrating LLMs, retrieval pipelines, and agentic patterns with AI specialists. Set up observability and evaluation tooling to ensure traceability and iteratively improve product performance. Deploy solutions in cloud environments, balancing speed, robustness, and security while collaborating closely with clients to deliver tangible business impact. Work within a 20-person team at The Tech Collective, a Data & AI hub backed by Implement Consulting Group, focusing on end-to-end ownership of AI-first products.
Required Qualifications
- 5+ years of hands-on full-stack experience
- Strong full-stack foundation: solid skills in TypeScript and/or Python
- Experience building and shipping production systems
- Mentoring experience: helping other developers through technical sparring and code reviews
- A track record of building substantial solutions from scratch (e.g., startup, scale-up, or personal ventures)
- The ability to reason about architecture, data flows, trade-offs, and failure modes across the stack
- The ability to explain complex technical concepts clearly to non-technical stakeholders
- The ability to work across disciplines
- The ability to learn from – and share knowledge with – others in the team and across Implement
Desired Qualifications
- An AI builder mentality
- Comfortable owning applications end to end – from frontend and backend to data and deployment
- Outward curiosity: actively seeking to understand client problems in detail and working in close collaboration with them to solve them
- Ownership and leadership: taking responsibility for outcomes, and leading technical direction without relying on formal authority
- Critical technical judgement: a keen eye for identifying weaknesses in existing architectures and tech stacks, and knowing where and how to improve them
- Tool agnostic: capable of choosing the right tool for the job
- Experience setting up the right observability and eval tooling to establish traceability and iteratively improve on products
- Experience with event-driven or real-time features
- Experience integrating LLMs, retrieval pipelines, and agentic patterns into real products
- Experience designing data models
- Experience reasoning about distributed systems and trade-offs
- Experience deploying and operating solutions in cloud environments
- Experience balancing speed, robustness, and security
- Experience working closely with clients and stakeholders to create tangible business impact
- Experience collaborating with AI specialists who bring deep model and ML expertise
- Experience applying sound software engineering principles
- Experience using AI-assisted development tools thoughtfully and critically
- Experience making pragmatic decisions in ambiguous contexts
- Experience identifying weaknesses in existing architectures and tech stacks
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