Senior Software Engineer – AI Build and Deployment
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Job Description
Senior Software Engineer responsible for building and deploying AI solutions into applications. Collaborating with team on production-grade pipelines and engineering excellence practices.
Responsibilities:
- Design and build production-grade AI/LLM processing pipelines with a focus on reliability, throughput, and unit economics
- Own observability for AI workloads end-to-end
- Build and maintain the deployment and runtime infrastructure for these pipelines on AWS
- Establish CI/CD for AI services and models: automated testing, regression evals, safe rollouts and rollback paths
- Drive engineering excellence in the AI team — pipeline architecture patterns, versioning of prompts/models/datasets, reproducibility
- Partner with SRE, Platform, and Product Engineering to harden shared services
- Mentor engineers on building maintainable, testable AI systems; raise the bar on code review, design documents
Requirements:
- 7+ years building production distributed systems
- at least 2+ years operating AI/ML or LLM-based pipelines at scale
- Deep experience with AWS (EKS/Kubernetes, Lambda, Step Functions, event-driven patterns)
- Terraform or AWS CDK as a primary delivery mechanism
- Strong proficiency in Python (and ideally TypeScript/Node) with production patterns for async processing, backpressure, retries, and idempotency
- Proven track record with observability stacks (especially LGTM) applied specifically to probabilistic/LLM systems — evals, drift, hallucination detection, cost/latency SLOs
- Experience integrating with foundation model providers (Anthropic, OpenAI, Gemini) and/or self-hosted inference, including prompt management, caching, and guardrails
- Experience with vector stores, embeddings pipelines, and retrieval evaluation
- Helpful to have experience with workflow tools like Argo or Dagster
Benefits:
- flexible working hours
- time to take care of your physical and emotional well-being
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