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Job Description
The GenAI Architect is responsible for evaluating, designing, implementing, and strategizing AI solutions involving large language models and agentic AI, collaborating with cross-functional teams to solve business problems and drive innovation in a remote, multicultural environment.
Key Responsibilities
- Evaluate existing systems and processes to identify opportunities for GenAI improvements or solutions.
- Design, develop, and implement LLM-based GenAI applications and integrate them into existing products or services.
- Collaborate with stakeholders to align AI initiatives with business goals and analyze the impact of deployed solutions.
- Monitor, evaluate, and refine AI strategies using metrics and KPIs to ensure continuous improvement.
- Work closely with data scientists, engineers, and product teams to ensure AI solutions meet business objectives.
Requirements
- Demonstrated ability to take a GenAI application from ideation through design, prototyping, production deployment, monitoring, and iteration.
- Combined expertise in LLM engineering, RAG design, and agentic orchestration with production-grade software engineering and DevOps skills.
- Hands-on experience developing multimodal and Agentic RAG pipelines that involve parsing and retrieving from diverse data types such as text, images, charts, and documents.
- Knowledge of integrating vector databases, metadata filters, and graph-based memory structures to support complex reasoning.
- Ability to design and deploy agentic systems using industry-standard frameworks while effectively abstracting tools, including tool schemas and action layers.
- Understanding when to apply orchestration strategies such as ReAct versus planner-executor depending on use case requirements.
- Familiarity with wiring up tools like LangSmith, latency factuality metrics, and automated A/B testing in real-world pipelines.
- Experience in scalable and cost-conscious engineering, including balancing performance, scalability, and cost in LLMOps, token budgeting, usage quotas, and observability tools for tracing and optimization.
- Ability to manage trade-offs between classic NLP approaches and large-model heuristics when required by efficiency goals.
- Very strong communication and collaboration skills.
Benefits & Perks
100% remote work
Monthly WFH allowance
Career development program with 360º feedback
Allocated time for tech training (online courses, conferences, books, etc.)
Mentoring program (opportunities to be a mentor or mentee)
Access to Zartis Wellbeing Hub and Kara Connect platform for mental health, nutrition, physiotherapy, and fitness support
Multicultural working environment with online team-building activities
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