About the job
About Gapstars
Gapstars is a leading software development service provider based in the Netherlands, specializing in creating agile remote teams in Sri Lanka and Portugal for forward-thinking technology companies. With a vibrant community of over 300 TechStars and innovative professionals, we transform scalable software into high-performance products that redefine the future. Our partners are ambitious tech enterprises eager to dominate their markets.
About the Role
We are seeking a proactive AI Engineer to design, construct, and scale impactful generative AI systems that provide substantial value to both our customers and internal teams.
This position starts as a standalone AI role integrated within a robust, collaborative engineering culture. You will closely collaborate with product managers, software engineers, and stakeholders from customer support, marketing, and technology to swiftly and safely bring AI concepts into production, with a focus on measurable outcomes. The emphasis is on applied generative AI, utilizing modern LLMs, APIs, and agentic patterns to develop reliable, user-facing systems without the need to train foundational models from scratch.
What You’ll Work On
Customer Support AI Agent:
Develop and enhance an AI agent integrated with Salesforce to manage customer support inquiries, leveraging robust orchestration, tooling, and evaluation frameworks.AI for Marketing Enablement:
Assist the marketing team with AI-driven image editing and content workflows through prompt engineering, automation, and systematic evaluation.Internal AI Enablement:
Promote AI integration across the broader engineering organization by identifying opportunities, building prototypes, and operationalizing successful use cases.
Responsibilities
Design, build, and deploy production-grade AI systems utilizing modern LLM APIs and frameworks.
Implement agentic AI patterns, including tool use, planning, reflection loops, and multi-step workflows, selecting the appropriate complexity for each case.
Create evaluation frameworks (“evals”) to assess system quality, reliability, latency, user experience, and safety.
Develop and optimize RAG pipelines and context engineering strategies as needed, without defaulting to RAG for every challenge.
Coordinate AI workflows that integrate with existing systems (e.g., Salesforce, internal APIs, marketing tools).
Work closely with software engineers to ensure that AI systems adhere to robust engineering practices and are ready for production.
Manage AI solutions comprehensively, from experimentation and prototyping to deployment, monitoring, and iterative improvement.
Apply infrastructure-as-code, CI/CD, and observability principles to AI systems.
Act as a mentor for other engineers, guiding them in the application of AI technologies.
