AI Architect

About the Company
At Agilisum Consulting, we’re at the forefront of leveraging data and AI to revolutionize the Life science Industry. Our team is passionate about creating scalable, secure, and innovative data solutions to power next-generation applications. Join us to help shape cutting-edge systems that integrate generative AI into data architectures, enabling transformative insights and solutions for our clients and teams.

Key Responsibilities
As a Data Architect with Generative AI expertise, you will:
Design and implement  robust data architectures that support AI and machine learning (ML) workloads, including Generative AI applications.
Develop and optimize  data pipelines  for training, validating, and deploying AI models efficiently and securely.
Integrate AI frameworks  into data platforms, ensuring scalability, low latency, and high throughput.
Collaborate  with data scientists, AI engineers, and stakeholders to align data strategies with business goals.
Lead initiatives to ensure  data governance , security, and compliance standards (e.g., GDPR, CCPA) are met in AI-driven environments.
Prototype and implement  architectures that utilize generative models (e.g., GPT, Stable Diffusion) to enhance business processes.
Stay up to date with the latest trends in Generative AI, data engineering, and cloud technologies to recommend and integrate innovations.

Required Qualifications
We’re looking for someone with:
A  bachelor’s degree  in Computer Science, Data Engineering, or a related field (master’s preferred).
5+ years  of experience in data architecture, with a focus on AI/ML-enabled systems.
Hands-on experience with  Generative AI models  (e.g., OpenAI GPT, BERT, or similar), including fine-tuning and deployment.
Proficiency in  data engineering tools and frameworks , such as Apache Spark, Hadoop, and Kafka.
Deep knowledge of  database systems  (SQL, No

SQL) and  cloud platforms  (AWS, Azure, GCP), including their AI/ML services (e.g., AWS Sagemaker, Azure ML, GCP Vertex AI).
Strong understanding of  data governance ,  MLOps , and  AI model lifecycle management .

Experience with programming languages such as  Python  or  R  and frameworks like  Tensor Flow  or  PyTorch .
Excellent problem-solving and  communication skills , with a demonstrated ability to lead cross-functional teams.
Preferred Skills
Familiarity with  LLM fine-tuning ,  prompt engineering , and  embedding models .
Strong domain expertise in Life Science Industry
Experience integrating generative AI solutions into production-level applications.
Knowledge of  vector databases  (e.g., Pinecone, Weaviate) for storing and retrieving embeddings.
Expertise in  APIs for AI models , such as OpenAI API or Hugging Face Transformers.