NetCraftsmen, now BlueAlly

AI Engineer

• Design, build, and operate enterprise AI systems across our client portfolio.
• Work end-to-end across the AI stack — from inference engines and platform infrastructure up through application-level engineering.
• Lead end-to-end design, build, and operation of AI systems on AI Factory platforms across multiple client engagements.
• Engineer and tune LLM inference serving stacks — primary depth in vLLM with breadth across the inference ecosystem — for client latency, throughput, and cost targets.
• Tune inference performance through KV cache management, paged attention, batching strategies, and Dynamo-based disaggregated serving.
• Architect and operate MLOps pipelines covering model lifecycle, registries, deployment, rollback, and observability.
• Design and engineer RAG applications on top of vector databases.
• Build and tune prompt-engineering patterns at production scale.
• Engineer high-performance storage and networking for AI workloads.
• Operate Kubernetes clusters underpinning AI workloads.
• Build and maintain container images, registries, and CI/CD pipelines for AI/ML services.
• Implement monitoring, alerting, logging, and capacity planning across the AI stack.
• Harden environments to meet client security and compliance requirements.
• Lead troubleshooting across various environments and technologies.
• Engage directly with client stakeholders — technical and executive — to communicate status, root cause, options, and recommendations.
• Mentor and code-review work from less senior engineers; raise the technical bar of every engagement you join.
• Author runbooks, reference architectures, and knowledge base content; lead client knowledge transfer and enablement sessions.
• Participate in on-call rotation and incident response for production AI workloads.
• Contribute reusable patterns, tooling, and reference designs back to the practice.

Senior AI Engineer