What are the responsibilities and job description for the Senior Fullstack AI/ML Engineer position at Jobs via Dice?
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Skill Rating
Agentic Orchestration
Production RAG
Asynchronous UI/UX
AI Observability
AI Security/Guardrails
Role Overview
We are looking for a Senior Fullstack Engineer who views LLMs as a component of a larger system, not a standalone solution. You will build agentic workflows where the challenge isn t just talking to an AI, but managing state, ensuring reliability, and creating seamless human-in-the-loop interfaces.
Key Responsibilities
Skill Rating
Agentic Orchestration
Production RAG
Asynchronous UI/UX
AI Observability
AI Security/Guardrails
Role Overview
We are looking for a Senior Fullstack Engineer who views LLMs as a component of a larger system, not a standalone solution. You will build agentic workflows where the challenge isn t just talking to an AI, but managing state, ensuring reliability, and creating seamless human-in-the-loop interfaces.
Key Responsibilities
- Agentic Orchestration: Design and implement complex chains and graphs (using LangGraph, LangChain, or equivalent) that manage multi-turn reasoning and tool-calling.
- System Architecture: Develop the connective tissue between LLMs, Vector Databases (e.g., Pinecone, Weaviate), and legacy relational databases.
- Production UX: Build React-based interfaces that handle asynchronous streaming, partial state updates, and Human-in-the-loop (HITL) correction UI.
- Observability & Evaluation: Implement LLM-Ops patterns tracing requests (LangSmith/Arize), monitoring for hallucinations, and managing prompt versioning as code.
- Secure Integration: Architect secure API gateways that handle rate-limiting, token-cost management, and PII masking before data reaches an LLM.
- 5 Years Professional Engineering: Deep proficiency in Python (FastAPI/Pydantic) and at least one other ecosystem (Java/Spring or .NET).
- Modern Frontend: 3 years of React/TypeScript, specifically handling complex state management (Redux/Zustand) and real-time data (WebSockets/SSE).
- Orchestration Mastery: Proven experience building agentic workflows you must be able to explain how to handle loops, memory persistence, and tool-error recovery.
- AI Patterns: Practical experience with RAG (Retrieval Augmented Generation) beyond the tutorial level handling chunking strategies, embedding drift, and re-ranking.
- DevOps/SDLC: Strong Git hygiene, CI/CD experience, and a test-first mentality for both traditional code and LLM prompts.