Software AI Engineer – Agentic AI-1
Role summary
The Software AI Engineer – Agentic AI role is a full-time, onsite position in New York, NY. This role requires 10+ years of experience in building large-scale distributed systems and strong expertise in LLM systems, agentic workflows, or advanced ML infrastructure. The engineer will own complex, cross-cutting agentic systems, leveraging deep experience across the agentic AI stack including planning, tool use, memory, and evaluation. Key responsibilities include driving technical direction, designing and operating production-grade agentic AI systems, and mentoring senior engineers. Proficiency in Python, Go, TypeScript, cloud platforms (AWS/GCP), Kubernetes, event-driven architectures (Kafka), and orchestration frameworks like LangChain is essential.
New York, New York 10001 Posted April 1st, 2026
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Job Type: Full Time
Job Category: IT
Job Description
Job Title : Software AI Engineer – Agentic AI
Location : New York, NY (ONSITE)
FTE ONLY
Job Description
- 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure
- Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
- Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
- Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
- Fluency with AI-assisted and agentic development workflows.
- Comfort operating in ambiguous problem spaces and translating them into shipped, reliable autonomous systems.
- Ability to influence technical direction and align teams without formal authority.
- Experience in workflow engines, async processing, queues, and streaming systems.
- Languages: Python, Go, TypeScript
- APIs and services: REST, gRPC
- Cloud and infrastructure: AWS and/or GCP, Kubernetes
- Distributed systems: event-driven architectures, including Kafka
- Orchestration Frameworks: LangGraph, LangChain, AirFlow, etc
- Integration of commercial and open-source LLMs into agentic workflows
- Agent and orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitives
- Model-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to TensorFlow
- Strong schema, validation, and state management practices using tools such as Pydantic (Python) and Zod (TypeScript)
- Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.
- Design, build, and operate production-grade agentic AI systems used across multiple products.
- Own and evolve shared agentic AI capabilities, including:
- Agent frameworks and orchestration layers
- Planning, tool use, and memory strategies
- Retrieval and grounding (RAG) pipelines
- LLM infrastructure, inference, and model gateways
- Evaluation, observability, and safety tooling for autonomous systems
- Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.
- Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to pro duction.
- Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.
- Mentor senior engineers and raise the technical bar for agentic AI development through example and influence.
Required Skills
CLOUD SECURITY ENGINEER
SENIOR EMAIL SECURITY ENGINEER