Software AI Engineer
Role summary
We are seeking a Software AI Engineer with extensive experience in building large-scale distributed systems and a strong focus on LLM systems, agentic workflows, or advanced ML infrastructure. The ideal candidate will have proven ownership of complex, cross-cutting agentic systems and deep engineering fundamentals across backend, APIs, data pipelines, and cloud infrastructure. Responsibilities include driving technical direction, designing and operating production-grade agentic AI systems, and evolving shared capabilities like agent frameworks, planning, memory, RAG pipelines, and LLM infrastructure. This role involves leading technical design reviews, mentoring senior engineers, and evaluating emerging AI trends to drive practical improvements.
Job Description
Software AI Engineer – Agentic AI
- 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.
Salary Range- $100,000-$120,000 a year
Qualifications:
BACHELOR OF COMPUTER SCIENCE
