AI AWS engineer- Bedrock

Seeking  to fill in a AI cloud  engineer  for   immediate remote contract opportunity with  my direct client  in Cincinnati OH  with excellent exp in AWS Bedrock, using foundational models for novel analysis and solutions,information security, APIs/Integrations ,Python,Chatbot,RAG experience .

If interested , share your word document resume, work authorization, expected hourly pay rate,  current location, availability for remote /hybrid work  , skill stack and LinkedIn.

Reach me for more details. thanks.

If not, Appreciate any referrals.

 TECHNICAL SKILLS

Must Have

2–5 years of experience in AI/ML engineering, data engineering, or software engineering roles

AWS Bedrock (foundation models ,model provisioning, API integration, prompt configuration, model evaluation)

AWS (Lambda, S3, CloudWatch, Step Functions, or DynamoDB)

Experience implementing workflows that incorporate humanintheloop validation or approval steps

Exposure to cyber security concepts such as detection engineering, incident response, threat intelligence, or security operations

Python (interacting with AI/LLM APIs and building smallscale automation or orchestration components)

Understanding of secure AI development practices, including safe prompt design and datahandling minimization

Experience with RAG patterns, vector databases, or embeddings

Familiarity with model safety evaluations or responsible AI frameworks

Prior work building prototypes or proofofconcept AI tools

Understanding of secure coding principles and adversarial AI risks

Job Summary

We are seeking a midlevel AI Cloud data Engineer (Contractor) to support our Cyber Threat Interdiction team with the development and execution of AI experiments using AWS Bedrock. The contractor will collaborate with engineering and a cross-functional threat interdiction team with building secure, costefficient AI workflows and prototype solutions that advance the bank’s cyber defense mission.

This role is wellsuited for someone with handson AWS Bedrock experience, solid data engineering or data science foundations, and an interest in applying AI capabilities to cyber security use cases.

Key Responsibilities

Assist in designing, building, and testing AI experiments leveraging AWS Bedrock and external lab environments, including model selection, prompting strategies, and orchestration patterns.

Develop AI and MCPrelated code using secure practices to minimize risks related to model context sharing and tool invocation.

Implement and maintain humanintheloop processes to ensure responsible oversight of AI and agent workflows.

Support data preparation, pipeline construction, and costmonitoring tasks to ensure experiments run within allocated usage budgets.

Apply cyber security knowledge to help shape experiments that support threat detection, interdiction, and operational security goals.

Document experiment configurations, testing outcomes, risks, and recommended next steps.

Contribute to reusable templates, runbooks, and guardrails that help the team scale its AI experimentation safely.

Required Skills:

8+ years of IT experience with 2–5 years of experience in AI/ML engineering, data engineering, or software engineering roles.

Handson experience working with AWS Bedrock (model provisioning, API integration, prompt configuration, model evaluation).

Proficiency in Python, including interacting with AI/LLM APIs and building smallscale automation or orchestration components.

Understanding of secure AI development practices, including safe prompt design and datahandling minimization.

Experience implementing workflows that incorporate humanintheloop validation or approval steps.

Exposure to cyber security concepts such as detection engineering, incident response, threat intelligence, or security operations.

Experience working with AWS services such as Lambda, S3, CloudWatch, Step Functions, or DynamoDB.

Experience with RAG patterns, vector databases, or embeddings.

Familiarity with model safety evaluations or responsible AI frameworks.

Prior work building prototypes or proofofconcept AI tools.

Understanding of secure coding principles and adversarial AI risks.