ML Ops Engineer

Job Title - MLOps Engineer

Location- Reading Pennsylvania Work from Client location 5 days a week

Looking for a pure MLOps Engineer with hands-on experience in Dataiku (Sage Mager is plus).

Responsibilities

Design multi-agent architectures: define agent roles (planner researcher retriever executor reviewer) toolboxes handoffs memory strategy (short/long-term) and supervisor policies for safe collaboration.
Build high-quality RAG: implement ingestion chunking embeddings indexing and retrieval with evaluation (precision/recall groundedness hallucination checks) guardrails and citations.
Productionize on AWS: leverage services like Bedrock (Agents/Knowledge Bases/Flows) Lambda API Gateway S3 DynamoDB OpenSearch/Vector DB Step Functions and CloudWatch for tracing and alerts.
MLOps/LLMOps: automate CI/CD (GitOps) containerization (Docker/Kubernetes) infra-as-code secrets/IAM blue green/rollbacks and data/feature pipelines.
Observability & evaluation: instrument telemetry (traces token/cost latency) build dashboards (Grafana/CloudWatch) add human-in-the-loop review A/B testing and continuous offline/online evals.
Operate reliably at scale: implement caching rate-limit management queueing idempotency and backoff; proactively detect drift and degradation.
Collaborate & communicate partner with infra/DevOps/data/architecture teams; document designs SLIs/SLOs runbooks; present status and insights to technical and non-technical stakeholders.
Qualifications we seek in you!
Minimum Qualifications
Bachelors degree in computer science Data Science Engineering or related field-or equivalent experience.
Proven experience building agentic systems (single or multi-agent) and RAG pipelines in production.
Strong cloud background for AI/ML workloads; familiarity with Bedrock or equivalent LLM platforms.
Solid CI/CD and containerization skills (Git Docker Kubernetes) and infra-as-code fundamentals.
Knowledge of data governance and model accountability throughout the MLOps/LLMOps lifecycle.
Excellent communication collaboration and problem-solving skills; ability to work independently and within cross-functional teams.
Passion for Generative AI and the impact of agent-based solutions across industries.
Preferred / Good to Have
Experience with AWS Bedrock Agents/Knowledge Bases/Flows OpenSearch (or other vector databases) Step Functions Lambda API Gateway DynamoDB S3.
Dataiku platform exposure-govern approvals artifacts MLOps deployment flows; SageMaker for custom model hosting.
Familiarity with agent frameworks (e.g. LangGraph crewAI Semantic Kernel AutoGen) and evaluation frameworks (guardrails groundedness hallucination checks).
Covered these Dataiku Certifications (nice to have): ML Practitioner Advanced Designer MLOps Practitioner.

Note: Momento USA is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex pregnancy sexual orientation gender identity national origin age protected veteran status or disability status.