Gen AI Engineer

problem - solving and communication skills

performance optimization

Dev Ops & CI/CD

Python

LLM Concepts

Lang Chain/Lang Graph

We are seeking a highly skilled GenAI Agentic AI Engineer with strong hands‑on experience in Deep Agent Frameworks Lang Chain Lang Graph and Claude models to design and build next generation agentic AI solutions.

The role requires deep Python expertise, strong exposure to AWS native data and AI services, and practical experience in building multi‑agent autonomous tools using AI systems for enterprise scale use cases.

The ideal candidate will have a solid foundation in Generative AI concepts, experience operationalizing agents on cloud platforms, and the ability to design scalable, secure, and explainable AI workflows.

• Design, develop and deploy agentic AI solutions using Deep Agent Frameworks Lang Chain and Lang Graph.
• Build multi‑agent workflows leveraging LLMs Claude via Amazon Bedrock for reasoning orchestration and task execution.
• Develop robust Python‑based services and pipelines for GenAI and AI‑driven automation use cases; integrate agents with AWS data services Glue, Athena, S3, etc. for retrieval, processing and analytics.
• Implement RAG Retrieval Augmented Generation and tool‑enabled agent patterns; ensure solutions are scalable, secure, auditable and production ready.
• Collaborate with data platform and product teams to translate business problems into agent‑based AI architectures.
• Contribute to architecture decisions, technical standards and reusable frameworks for GenAI and agent ecosystems.
• Support model governance, prompt versioning, observability and performance optimization.

Strong proficiency in Python, enterprise‑grade production quality code; experience building APIs, microservices and backend services for AI workloads; solid understanding of object‑oriented design, async processing and modular architectures.

• Deep Agent Frameworks
• Lang Chain
• Lang Graph
• Experience building autonomous agents and multi‑agent systems
• Stateful and event‑driven agent flows

• Prompt engineering and prompt orchestration
• Chain of thought and reasoning‑based approaches
• Tool‑augmented LLMs
• RAG patterns
• Practical experience with Claude models via Amazon Bedrock
• Familiarity with evaluation, hallucination mitigation and response quality control

• Amazon Bedrock (LLM hosting and orchestration)
• Amazon Athena (querying structured and unstructured data)
• Amazon S3 (data lake and document stores)
• Experience designing and deploying AI solutions in a cloud‑native environment; understanding of IAM, security, logging and cost optimization for AI workloads

The candidate must demonstrate strong agentic AI expertise, including: building agents from scratch (not just consuming APIs); designing agents with goal‑driven reasoning, tool invocation, memory and state management, multistep task decomposition; implementing multi‑agent collaboration and orchestration patterns; designing agent systems that interact with APIs, databases, files, documents and enterprise data sources; familiarity with agent observability, failure handling and explainability; and the ability to translate business workflows into agent‑based execution plans.

The pay range that the employer in good faith reasonably expects to pay for this position is $40.45/hour – $63.20/hour. Our benefits include medical, dental, vision and retirement benefits.

Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for…