Design, build, and deploy production-grade agentic AI systems, including autonomous and multi-agent architectures, tool-use orchestration, memory, retrieval, and function-calling workflows. Integrate agents with enterprise tools and databases, implement evaluations, guardrails, observability, fallback paths, and human-in-the-loop controls. Lead technical strategy, client collaboration, prototyping, and product direction for enterprise AI initiatives.
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.
100% Remote (Full-Time)Key Responsibilities- Agentic System Architecture & Orchestration
- 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.
- Enterprise Integration & Tool 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.
- Productionization, Reliability & Observability
- 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.
- Technical Leadership & Client Strategy
- 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.
- Core Python Engineering: Expert-level Python skills with a track record of building scalable, asynchronous, production-grade systems.
- Agentic AI & Orchestration: Direct experience building and productionizing agentic frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI, LlamaIndex, or custom in-house agent loops).
- LLM Tooling & Function Calling: Strong understanding of structured outputs, JSON mode, tool calling, multi-step reasoning, and context window management.
- Retrieval & Memory Architectures: Hands-on experience with vector search engines (Pinecone, Qdrant, Weaviate, pgvector), embeddings, and RAG/advanced memory retrieval patterns.
- Production Guardrails & Evals: Practical experience evaluating agent performance, tracking telemetry (e.g., LangSmith, Phoenix, Weights & Biases), and implementing safety guardrails.
- High-Autonomy Execution: Ability to navigate ambiguity, drive technical strategy, and deliver end-to-end features independently.
- Multi-Agent Collaboration: Experience building systems where specialized agents collaborate, delegate, or critique outputs hierarchically.
- Cloud-Native & Distributed Systems: Experience with event-driven architectures, serverless functions, and cloud platforms (Azure AI, AWS Bedrock, GCP Vertex AI).
- Enterprise Security: Understanding of RBAC, data privacy, and secure execution sandboxes for code-interpreter agents.
This role is based in the US and only open to citizens and permanent residents of the US who do not require visa sponsorship.
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