Senior MLOps Engineer — AWS Bedrock / LLM / Agentic AI
Contract evidence involving Python, Docker, AWS. First observed 20 Oct 2026; the response opens on freelancermap.com.
- Budget
- Not provided by source
- Work format
- Contract
- Role family
- AI / ML engineer
- Seniority
- Senior
- Observed
- 20 Oct 202633 hours old
- Deadline status
- Deadline not provided — verify source
- Response destination
- freelancermap.com
Opportunity summary
Senior MLOps Engineer — AWS Bedrock / LLM / Agentic AI. The source classifies this as contract work involving Python, Docker, AWS, RAG, Monitoring and alerting. Location or remote eligibility: International competition and remote delivery are allowed, but the listing explicitly requires direct applicants only and says no agencies or intermediaries..
Technology and scope
The reported stack is AWS Bedrock, AgentCore, SageMaker, Python APIs, RAG, agents, knowledge bases, vector stores, guardrails, Docker, Kubernetes, Kubeflow, MLflow, Terraform, CloudFormation, Step Functions, ECS, Spark, Airflow, Kafka, CI/CD, observability. Check the source for required versions, deliverables and which technologies are mandatory.
Engagement details
Contract: time-bounded or ongoing contractor capacity. Source timing: Two complementary projects, each 40 days; 50% each or one consultant at 100%; total effort to be confirmed; 80% overlap with 08:30–17:00 CEST
Budget
Budget not provided by source. Confirm the rate or project value before preparing a proposal; no estimate has been substituted.
Dates and availability
First observed by Leadiy on 20 Oct 2026, 22:57 UTC. Public since 22 Oct 2026, 07:00 UTC. Deadline not provided — verify source. A listed deadline does not confirm that applications are still accepted. These are observation and publication dates, not a reconstruction of the source posting date. Date-only deadlines have no supplied timezone; the date changes here at midnight UTC.
Related market context
In the current 30-day Hiring Pulse, Python appears in 196 of 622 observed opportunities (31.5%). Counts are multi-label, so one opportunity may contribute to several technology buckets. This is a separate aggregate sample, not a confirmation of this opportunity’s availability.
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