| AI Engineer at Remote, Remote, USA |
| Email: [email protected] |
|
http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=3414035&uid=904a4ededf5a42b8ad617b1e080d63c8 Role: AI Engineer Location: Auburn Hills, MI, 48326 Duration: 1 Year Rate:$35 on C2C 100% On-Site Role Descriptions: Problem-Solving & Critical Thinking: Ability to analyze complex| ambiguous problems and design innovative| practical solutions. Thrives in navigating the uncertainty inherent in emerging AI technologies. Collaboration & Communication: Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. Proven experience working cross-functionally with product| research| and infrastructure teams. Ownership & Leadership: A bias for action and a strong sense of ownership. Capable of driving projects from conception to completion| mentoring junior engineers| and helping to define and influence AI strategy and best practices Essential Skills: Core Engineering & Programming: Strong software engineering fundamentals with expert-level proficiency in Python. Experience with Java| Go| or TypeScript is a strong plus. LLM & GenAI Application Development: Proven| hands-on experience building and deploying production-grade applications using Large Language Models (LLMs) like GPT| Claude| or Gemini. This must go beyond simple API calls and include experience with tool/function-calling| structured outputs| and evaluation. Agentic AI Frameworks & Orchestration: Demonstrable expertise in designing and implementing agentic workflows using frameworks like LangGraph| Semantic Kernel| AutoGen| or similar. Experience with multi-agent systems| planning| and autonomous execution is critical. RAG (Retrieval-Augmented Generation): Deep| practical knowledge of building and optimizing RAG pipelines. This includes data ingestion| various chunking strategies| embeddings| vector databases (e.g.| Pinecone| Chroma| FAISS)| and hybrid search/reranking. Production & MLOps: Experience with production engineering practices| including building scalable APIs (REST| RPC)| microservices| CI/CD pipelines| containerization (Docker| Kubernetes)| and cloud platforms (AWS| Azure| or GCP). Agentic System Design & Engineering: Architect| build| and deploy advanced AI agents capable of autonomous reasoning| decision-making| and self-directed task execution. Design and implement complex| multi-step agentic workflows that integrate with enterprise APIs| data sources| and platforms. RAG and Grounding Implementation: Develop robust RAG pipelines to ground agent responses in factual| reliable data. This includes managing the full lifecycle from data ingestion and vectorization to retrieval and citation. Tooling and Integration: Build and maintain the "tools" that agents use to interact with the digital world. Create secure| well-documented tool interfaces for internal services| databases| and third-party APIs.Evaluation| Guardrails & Safety: Design and implement comprehensive evaluation frameworks to measure agent performance| accuracy| and reliability. Develop and enforce safety guardrails| policy checks| and fallback mechanisms to ensure agents operate safely and predictably in production environments. Optimization and Productionization: Debug| monitor| and optimize agentic systems for latency| cost| and efficiency. Own the end-to-end deployment process| including CI/CD| structured logging| and incident response for AI systems. Desirable Skills: Keyword: Skills: AI Agents Experience Required: 8-10 Best Regards, Ankitha Papana , [email protected] -- Keywords: continuous integration continuous deployment artificial intelligence information technology golang California Michigan AI Engineer [email protected] http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=3414035&uid=904a4ededf5a42b8ad617b1e080d63c8 |
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| 10:54 PM 01-Jun-26 |