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AI Engineer – AWS & Amazon Bedrock
LinkedIn Recruiter Post
Experienced AI Engineer needed to design and deploy enterprise - grade Generative AI solutions using AWS cloud - native technologies, LLMs, and Amazon Bedrock.
About the role
- Staff Generative AI Engineer specializing in Generative and Agentic AI applications. Developing scalable AI systems and mentoring engineering talent.
Responsibilities
- Design, build, and ship production-grade Generative and Agentic AI applications and services for internal and external users
- Develop high-quality backend services in Python, with strong software engineering rigor around testing, performance, and maintainability
- Champion reusability and abstraction in everything you build by designing and building modular, well-abstracted components and libraries
- Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
- Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
- Build clean, well-tested RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance
- Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
- Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
- Contribute to platform architecture decisions and engineering best practices
- Take applications from prototype through production deployment, hardening, and ongoing operation
- Mentor and coach junior and mid-level engineers through code reviews, architecture discussions, and pair programming
- Foster a culture of engineering excellence, knowledge sharing, and continuous improvement
- Participate in technical design reviews and contribute to the professional growth of team members
Requirements
- 10-15 years of professional software engineering experience with at least 3-5 years of experience building AI/ML software products
- Bachelor’s degree in Computer Science or a related field (Master’s degree preferred)
- Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
- Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
- Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
- Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
- Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
- Strong understanding of API design, distributed systems, and cloud-native architecture
- Proven track record of taking systems from design through production deployment and operation
- Experience with containerization and orchestration (Docker, Kubernetes)
- Knowledge of Generative AI Risk Management frameworks (NIST RFM)
- Experience supporting developer platforms or internal tooling
- Experience writing design documents or helping define engineering standards
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