Senior Angentic AI Engineer

ImagineX Consulting•Remote, United States,

6d•Remote

About The Position

ImagineX is a tech company that deploys AI-assisted teams to build and secure mission-critical enterprise solutions with our clients – spanning software, data, and AI. Structured like a software company, not a traditional consultancy, we blend deep technical expertise with authentic values, achieving world-class satisfaction (NPS 91). Our dedicated teams specialize in software, data, and AI across the U.S. and LATAM, bridging the gap between boutique agility and enterprise scale. We are seeking a Senior AI Software Engineer with deep hands-on experience designing, building, and deploying Agentic AI systems in production. This is not an “AI-curious” or purely experimental role—we are looking for a practitioner who has shipped autonomous agentic architectures, understands the complex realities of productionizing LLM-driven workflows (reasoning loops, state management, tool-use orchestration, and guardrails), and can directly shape both technical and product direction.

Requirements

Expert-level Python skills with a track record of building scalable, asynchronous, production-grade systems.
Direct experience building and productionizing agentic frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI, LlamaIndex, or custom in-house agent loops).
Strong understanding of structured outputs, JSON mode, tool calling, multi-step reasoning, and context window management.
Hands-on experience with vector search engines (Pinecone, Qdrant, Weaviate, pgvector), embeddings, and RAG/advanced memory retrieval patterns.
Practical experience evaluating agent performance, tracking telemetry (e.g., LangSmith, Phoenix, Weights & Biases), and implementing safety guardrails.
Ability to navigate ambiguity, drive technical strategy, and deliver end-to-end features independently.

Nice To Haves

Experience building systems where specialized agents collaborate, delegate, or critique outputs hierarchically.
Experience with event-driven architectures, serverless functions, and cloud platforms (Azure AI, AWS Bedrock, GCP Vertex AI).
Understanding of RBAC, data privacy, and secure execution sandboxes for code-interpreter agents.

Responsibilities

Design, build, and deploy production-grade autonomous agent systems, multi-agent frameworks, and stateful orchestration pipelines in Python.
Implement tool-use reasoning loops, dynamic planning, function-calling patterns, and memory architectures (short-term, long-term, semantic memory).
Evaluate, benchmark, and integrate state-of-the-art foundation models (OpenAI, Anthropic, open-weight models) with a focus on latency, cost, determinism, and reasoning capabilities.
Connect autonomous agents securely to enterprise tools, databases, APIs, and external execution environments.
Build robust retrieval pipelines, hybrid search systems, and vector databases to supply real-time context to agentic workflows.
Implement evaluation frameworks (evals), guardrails, tracing, and observability to monitor agent behavior, handle edge cases, prevent hallucinations, and ensure deterministic outputs in production.
Design fallback mechanisms, human-in-the-loop (HITL) execution paths, and retry logic for high-reliability enterprise environments.
Own the end-to-end technical direction for AI initiatives, translating complex business challenges into production-ready agentic architectures.
Partner with client leaders and internal engineering teams to shape product roadmaps for enterprise AI execution.
Lead rapid prototyping and continuous experimentation to validate novel agent capabilities before scaling.