Principal GenAI Systems Engineer
Principal GenAI Systems Engineer
Posted on :
13-05-2025
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1 Vacancy
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Job Description
This is a remote position.
We are seeking a Principal GenAI Systems Engineer to join our team. Y ou will be responsible for designing developing and deploying applications that leverage generative AI models. You will work closely with company founders machine learning engineers (DataML Engineers) and software engineers to develop a specialized and scalable generative AI application interfacing with telemetryfocused AI products. Your role will involve both frontend and backend development ensuring seamless functionality and performance consistency for a unique implementation of Retrieval Augmented Generation (RAG). A significant aspect of this role will involve architecting engineering implementing and testing system prompting configurations and pipelines which are essential for unlocking the vast insights of company AI products for downstream automated Actions and semiautonomous Agents.
Responsibilities:
- Design configure and optimize the GenAItech stack including: LLM Vector DB Encoder / Decoder Vector Search (ANN HNSW) prompt framework and supporting cloud compute and service resources.
- Design and implement RAG pipelines that enhance generative AI models by integrating external data sources.
- Architect and engineer efficient retrieval systems that can fetch relevant data from databases knowledge graphs or external APIs to augment AIgenerated responses.
- Develop prompting pipelines that leverage context and retrieved information to generate accurate and contextually relevant responses.
- Collaborate with machine learning engineers to implement advanced techniques such as vector search semantic search and embeddings to improve data retrieval accuracy.
- Build and maintain robust pipelines for data retrieval preprocessing and integration into the generation process.
- Implement automated testing frameworks to validate the performance of RAG and prompting pipelines.
- Ensure that the retrieval and generation pipelines are scalable reliable and maintainable.
- Continuously monitor and refine pipelines to improve efficiency and reduce latency.
- Implement monitoring logging and alerting to maintain system health and uptime
- Collaborate with crossfunctional teams including UX/UI designers product managers and DevOps engineers to deliver highquality products.
- Collaborate with DataML Engineers Integration Engineers & GenAI Engineers for customerspecific deployments & configurations
- Write clean maintainable code and conduct code reviews.
- Document technical architecture processes and best practices.
Requirements
- Bachelor s or Master s degree in Computer Science Engineering or a related field.
- A strong foundation in software engineering principles is essential.
- Additional coursework or certifications in AI/ML or data science is a plus.
- 5 years of professional experience in complex systems engineering with a strong focus on AIdriven applications.
- Proven experience in integrating and deploying machine learning models particularly in generative AI (e.g. GPT GANs VAE etc.).
- Demonstrated experience in architecting engineering and deploying RAG pipelines for generative models and complex prompting systems.
- Familiarity with Pythonbased APIs.
Advanced Qualifications Nice to have:
- Masters degree in Computer Science Software Engineering or a related field.
- Experience with scalable and highperformance application development in a cloud environment (AWS GCP Azure).
- Familiarity with technologies and/or data architectures such as: Product Analytics (e.g Pendo Mixpanel) and Observability systems (e.. Grafana New Relic Dynatrace).
Benefits
- Work Location: Remote
- 5 days working
Bachelor s or Master s degree in Computer Science, Engineering, or a related field. A strong foundation in software engineering principles is essential. Additional coursework or certifications in AI/ML or data science is a plus. 5+ years of professional experience in complex systems engineering, with a strong focus on AI-driven applications. Proven experience in integrating and deploying machine learning models, particularly in generative AI (e.g., GPT, GANs, VAE, etc.). Demonstrated experience in architecting, engineering and deploying RAG pipelines for generative models and complex prompting systems. Familiarity with Python-based APIs. Advanced Qualifications - Nice to have: Masters degree in Computer Science, Software Engineering or a related field. Experience with scalable and high-performance application development in a cloud environment (AWS, GCP, Azure). Familiarity with technologies and/or data architectures such as: Product Analytics (e.g Pendo, Mixpanel), and Observability systems (e.. Grafana, New Relic, Dynatrace).
Employment Type
Full Time
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