GenAI Engineer

GenAI Engineer


Location: 100% remote


Term: 6 month contract plus extension

• Demonstrated experience with AWS Bedrock in real implementations (proof-of-concept through production).
• Strong understanding of Generative AI concepts, including:
  • RAG
  • Vector databases
  • Agent orchestration
  • Guardrails / safety controls
• Strong Python development experience (building services, APIs, or pipelines).
• Experience with AI/ML frameworks and tooling (including Langfuse or similar evaluation/observability tooling).
• Solid background in cloud architecture and DevOps practices supporting production systems.

• Design, build, and deploy GenAI applications using AWS Bedrock and related AWS services.
• Implement Retrieval-Augmented Generation (RAG) patterns including document ingestion, embedding strategies, chunking, retrieval tuning, and evaluation.
• Integrate and manage vector databases (selection, indexing strategy, performance tuning, and lifecycle management).
• Build and orchestrate agentic workflows (tool use/function calling, multi-step reasoning flows, agent orchestration patterns).
• Implement guardrails and safety controls (prompt/content filtering, policy enforcement, PII handling, secure prompt practices, and monitoring).
• Develop backend services and pipelines in Python to support AI workflows and integrations.
• Apply AI/ML tooling and frameworks (e.g., Langfuse for observability/evaluation and related AI frameworks as needed).
• Collaborate with engineering, product, and stakeholders to translate business requirements into technical designs.
• Support Cloud Architecture activities: solution design, cost/performance considerations, security, scalability, and reliability.
• Enable production readiness via DevOps: CI/CD, infrastructure-as-code, monitoring/alerting, deployment automation, and environment management.