- Company Name
- The Portfolio Group
- Job Title
- AI Platform Engineer
- Job Description
-
Job title: AI Platform Engineer
Role Summary: Own and evolve a cloud-native platform that powers conversational and generative AI products. Design, build, and operate runtime, infrastructure, and operational layers for RAG pipelines, LLM orchestration, vector search, and evaluation workflows across AWS and Databricks. Ensure scalability, observability, security, and cost efficiency for production‑grade AI services.
Expactations: Deliver end‑to‑end AI system capabilities that transform experimental models into reliable, scalable services. Collaborate with senior AI engineers and product teams to define architecture, implement observability, CI/CD, governance, and future multi‑model or agentic workflows.
Key Responsibilities:
- Own and continuously improve the AI platform for conversational assistants and generative AI offerings.
- Build, operate, and optimise RAG pipelines, LLM‑backed services, and vector search systems to enhance latency, reliability, and cost.
- Design and run cloud‑native AI services on AWS (Lambda, API Gateway, DynamoDB, S3, CloudWatch) and Databricks, including ingestion and embedding pipelines.
- Scale and maintain vector search infrastructure using Weaviate, OpenSearch, Algolia, and AWS Bedrock Knowledge Bases.
- Implement robust observability, CI/CD, security, and governance across AI workloads.
- Enable future architectures such as multi‑model orchestration and agentic workflows.
Required Skills:
- Strong experience with AWS services (Lambda, API Gateway, DynamoDB, S3, CloudWatch).
- Hands‑on Databricks and large‑scale data/embedding pipelines.
- Proven track record building and operating production AI systems: RAG pipelines, LLM services, vector search (Weaviate, OpenSearch, Algolia).
- Proficiency in Python; deploying containerised services on Kubernetes using Terraform.
- Deep understanding of distributed systems, cloud architecture, and API design with focus on scalability and reliability.
- Demonstrated ownership of observability, performance, cost efficiency, and operational robustness in production environments.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent professional experience).