- Company Name
- CloudHive
- Job Title
- Agentic AI Engineer
- Job Description
-
**Job title**
Agentic AI Engineer
**Role Summary**
Build and scale autonomous, agentic AI systems that make independent decisions, adapt user interactions, and drive operational efficiencies across multiple business domains. The role blends research, production engineering, and cross‑functional collaboration to move AI prototypes into reliable, cloud‑deployed solutions.
**Expectations**
- 5+ years in AI/ML engineering, with at least 2 years focused on agentic or autonomous systems.
- Proven track record of designing, implementing, and deploying multi‑agent architectures from concept to production.
- Deep familiarity with agentic frameworks (LangChain, LangGraph, ADK, custom runtimes), R.A.I.C. (ReAct, Chain‑of‑Thought) patterns, and integrating large language models via OpenAI, Anthropic, Azure OpenAI, Vertex AI, or on‑premises deployments (vLLM, TensorRT‑LLM, Ollama).
- Experience prototyping rapidly with tools such as Jupyter, Cursor, Windsurf, and converting prototypes into scalable services.
- Ability to design safe, sandboxed tool‑using AI systems with function‑calling, API integration, and secure execution.
**Key Responsibilities**
- Design, develop, and iterate autonomous agentic systems that perform tasks, interact with users, and adapt to changing conditions.
- Write clean, maintainable, scalable code following industry best practices and design patterns.
- Deploy AI workloads on cloud platforms (AWS, Azure, GCP) and manage infrastructure for performance, scalability, and reliability.
- Collaborate with architecture, product, security, and engineering teams to align technical solutions with business goals.
- Conduct research on emerging AI technologies, frameworks, and design principles to keep solutions innovative and future‑proof.
- Prototype new ideas quickly, validate them, and transition successful prototypes into production‑ready systems.
**Required Skills**
- Multi‑agent system design and implementation.
- Proficiency with agentic frameworks (LangChain, LangGraph, ADK) and ReAct/Chain‑of‑Thought patterns.
- Integration of LLMs via OpenAI, Anthropic, Azure OpenAI, Vertex AI, or on‑premises tools.
- Cloud deployment (AWS, Azure, GCP) and infrastructure management.
- Tool‑using AI expertise: function calling, API integration, safe sandbox execution.
- Strong problem‑solving, emergent behavior design, and production‑ready delivery.
- Familiarity with tool selection strategies and IDEs (Cursor, Windsurf) or notebooks (Jupyter).
**Preferred Skills**
- Agent orchestration and workflow platforms (Kubernetes, Airflow, Temporal, Agentspace).
- Event‑driven architectures (Kafka, RabbitMQ).
- Vector databases and knowledge systems (Pinecone, Weaviate, Chroma, Qdrant) and knowledge graph technologies (Neo4j, Amazon Neptune, Jena).
**Required Education & Certifications**
- Bachelor’s (or higher) degree in Computer Science, Electrical Engineering, or related field, or equivalent professional experience.
- No mandatory certifications required.