Senior Software Engineer – AI Build and Deployment

This is a fully remote position, open to applicants in Ireland.

📋 Description

• Create and develop production-quality AI/LLM processing pipelines with an emphasis on reliability, throughput, and cost efficiency.

• Take ownership of observability for AI workloads from start to finish.

• Construct and oversee the deployment and runtime infrastructure for these pipelines hosted on AWS.

• Implement CI/CD for AI services and models, including automated testing, regression evaluations, safe rollouts, and rollback strategies.

• Foster engineering excellence within the AI team by establishing pipeline architecture patterns, managing versioning of prompts/models/datasets, and ensuring reproducibility.

• Collaborate with SRE, Platform, and Product Engineering teams to strengthen shared services.

• Guide engineers in developing maintainable and testable AI systems; elevate standards in code reviews and design documentation.

⛳️ Requirements

• Over 7 years of experience in building production-level distributed systems.

• At least 2 years of experience managing AI/ML or LLM-based pipelines at scale.

• Extensive knowledge of AWS (including EKS/Kubernetes, Lambda, Step Functions, and event-driven architectures).

• Proficiency in Terraform or AWS CDK as a primary method of delivery.

• Strong skills in Python (and preferably TypeScript/Node), particularly in production patterns for asynchronous processing, backpressure, retries, and idempotency.

• Demonstrated experience with observability stacks (notably LGTM) applied to probabilistic/LLM systems — evaluations, drift detection, hallucination identification, and cost/latency SLOs.

• Familiarity with integrating foundation model providers (such as Anthropic, OpenAI, Gemini) and/or self-hosted inference, including prompt management, caching, and guardrails.

• Experience with vector stores, embeddings pipelines, and retrieval evaluation.

• Experience with workflow tools like Argo or Dagster is a plus.

🏝️ Benefits

• Flexible working hours.

• Time allocated for taking care of your physical and emotional well-being.