MLOps Engineer

MLOps Engineer – Join Our Team .job-posting-container {font-family: Arial, sans-serif; line-height: 1.6; color: #333; margin: 0; padding: 20px; background-color: #ffffff; box-sizing: border-box;} .job-posting-container * {box-sizing: border-box;} .job-posting-content {background-color: #ffffff; padding: 30px; max-width: 800px; margin: 0 auto; box-shadow: 0 0 10px rgba(0,0,0,0.1); border-radius: 10px;} .job-posting-container h1, .job-posting-container h2 {color: #004080; margin: 15px 0;} .job-posting-container h1 {font-size: 22px;} .job-posting-container h2 {font-size: 20px; border-bottom: 1px solid #ccc; padding-bottom: 5px; margin-top: 30px;} .job-posting-container ul {margin-left: 20px;} .job-posting-container .section {margin-bottom: 25px;} .job-posting-container .highlight {background-color: #eef6ff; padding: 15px; border-left: 4px solid #004080; margin-bottom: 15px; border-radius: 5px;} .job-posting-container strong {color: #333;} .job-posting-container li {margin-bottom: 8px;} MLOps Engineer Remote Position | USA | Full-time | $91/hour Position Overview You turn a working pipeline into a production system. The existing toolchain needs to be fully wired into CI/CD. You will enhance it with a proper evaluation and guardian pattern, and make the whole thing observable, auditable and affordable. Why Join Us? Work on cutting-edge AI and machine learning infrastructure at scale Opportunity to shape production LLM systems from the ground up Collaborative environment focused on engineering excellence and innovation Competitive compensation with flexible remote work arrangements Key Responsibilities Productionise the existing RAG and scanner toolchain through CI/CD — connecting the pipeline end to end so scans, dispositions and remediations flow without manual intervention Build the guardian / evaluation agent: an automated check that runs on every sub-agent deliverable, replacing the current brute-force knowledge-capture approach with a best-practice evaluation pattern Implement the deterministic assertion layer as a programmatic gate — automatically rejecting any disposition that contradicts its own evidence, before a human ever sees it Own AgentOps: trace capture, prompt / rule / model versioning, evaluation-in-CI, regression harnesses, and drift detection Build the observability the team watches daily: pending burn-down, auto-disposition rate, accuracy against the gold set, human-minutes per item, assertion-rejection rate and cost per item Own FinOps for the AI workload: model routing, delta-scoped runs, caching, and a per-cycle token budget tracked as a service-level objective Guarantee provenance and auditability for a regulated environment — every decision reproducible from its evidence snapshot, rule/prompt/model version and human verdict Qualifications 7+ years in platform / DevOps / MLOps engineering, including production LLM or ML workloads Python — production-grade CI/CD automation for application and ML/LLM workloads; release automation and test gating AgentOps / LLMOps — tracing, prompt versioning, evaluation in CI, regression harnesses, drift detection Observability — OpenTelemetry, distributed tracing, metrics and logging; building dashboards operators actually use AWS; containerisation; infrastructure-as-code (Terraform) FinOps for AI workloads — token accounting, model-routing economics, cost dashboards Guardrails and policy-as-code; secure handling of regulated data Working knowledge of Kubernetes; LangGraph; AWS Bedrock Guardrails Working knowledge of SQL; Informatica; evaluation-harness construction Ready to Apply? If you meet the qualifications and are excited about this opportunity, we encourage you to apply today. Contact: muthu@dprsolutionsinc.com Phone: 5719339984 Take the next step in your career!