Applied AI Engineer
Content + Source + Freshness • 13 Feb 2026 • 95% confidence
Offer value
Attractive due to the role's impact on AI-powered analytics and strong market relevance.
- Key role in AI-powered analytics transformation
- Strong industry presence with significant growth potential
- Focus on real-world applications and performance
Pros
- Direct involvement in AI feature deployment for analytics products.
- Opportunity to influence product development in a fast-paced environment.
- Highly relevant role in a growing field of AI analytics.
Cons
- Requires balancing between experimental work and production-grade implementation.
- Possibility of high expectations and pressure due to project timelines.
Who it's for
Mid to senior level (4+ years) • Hybrid options available
Good fit
- Backend developers with AI experience seeking impactful roles.
- Individuals who thrive in collaborative, dynamic settings.
- Professionals eager to apply technical skills to real-world problems.
Not recommended for
- Candidates with limited experience in backend systems.
- Individuals seeking primarily frontend or design roles.
- Those not interested in applying AI to commercial products.
Motivation fit
Key skills
About the job
Join Sisense. Build the Future of AI-Powered Analytics. Sisense is transforming business intelligence through embedded, developer-first analytics, and now, AI is becoming the foundation of our platform. We're scaling our AI platform capabilities to deliver AI-first experiences that feel intelligent, contextual, and reliable from the outset.
We’re seeking an exceptional Applied AI Engineer to lead the technical execution of AI-powered product features, from end-to-end. This is a backend-leaning role focused on agentic AI workflows and orchestration. This is not a research role. You’ll design, build, and own robust services that bridge cutting-edge generative AI capabilities and the real-world demands of a modern analytics platform.
What you’ll do:
- Design and deliver robust backend services and orchestration pipelines, such as Natural Language Query, that power AI features across the Sisense platform.
- Operationalize LLM-based and ML-driven logic, including prompt engineering and chaining into production-grade APIs.
- Own orchestration pipelines and agentic workflows, including multi-agent communication and modular tool execution.
- Integrate with platform infrastructure and AI services, including LLM gateways, vector databases, and centralized configuration tools.
- Collaborate cross-functionally with Software Engineers, Data Scientists, Infra Engineers, and Product Managers to ensure seamless handoff and transformation of experimental logic into reliable services.
- Drive internal tooling and reusable components to accelerate AI feature delivery across teams.
- Ensure high performance, scalability, and resilience of deployed AI-powered services.
What you bring:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience building production AI systems.
- 4+ years building production systems that integrate ML, LLMs, or AI workflows
- Strong proficiency in backend technologies such as Node.js, Python, or Go.
- Proven track record building APIs, orchestration systems, and pipelines supporting ML or LLM-based features.
- Familiarity with ai development frameworks such as LangChain, LangGraph, LangFuse, MLflow, or similar.
- Comfortable with cloud platforms (e.g., AWS, GCP, Azure) and DevOps practices.
- Understanding of distributed systems and scalable service design.
- Excellent collaboration skills and ability to communicate complex systems to both technical and non-technical stakeholders.
Preferred Skills:
- Experience with agentic systems or multi-agent orchestration in AI workflows.
- Exposure to Knowledge Graphs, RAG (Retrieval-Augmented Generation), or semantic search.
- Understanding of AI infrastructure components such as prompt lifecycle, fallback logic, and feature-level configuration.
- Familiarity with vector databases and AI observability practices.
Why This Role Matters
Your work will directly shape how Sisense users experience intelligence across the platform—from data modeling to dashboard creation to analytics insights. You won’t be a helper—you’ll be an owner. You’ll drive the creation of intelligent workflows, semantic reasoning tools, and contextual insight delivery inside a real product. You’ll push the boundaries of what’s possible in applied AI at scale—and help define how analytics products evolve in the AI-native era.
About Sisense:
Sisense is a pioneer in embedded analytics, and is now positioned as a leading Analytics Platform as a Service (AnPaaS) provider, helping developers and product teams infuse analytics intelligence into every product and workflow. Now, as we embrace the generative AI revolution, we’re scaling our vision to create an AI-first analytics platform that empowers users to ask, understand, and act on data with unprecedented ease and speed.
