SENIOR AGENTIC AI ENGINEER

ABOUT THIS JOB

• OmniPhi is building the first Integrated Agentic Trading Environment (IATE), bringing strategy research, development, testing, deployment, and live operation into one AI-native platform.
• We are hiring a Senior Agentic AI Engineer to improve our core agentic systems, including the agent harness, tool use, memory, context management, RAG, multi-agent coordination, reliability, and efficiency.
• This is a hands-on engineering role requiring experience building and improving production agentic systems beyond basic chatbots and API wrappers.

RESPONSIBILITIES

• Design, build, and continuously improve the core agent harness.
• Develop reliable tool creation and tool-calling systems across internal tools, external APIs, databases, and MCP connections.
• Implement structured outputs, tool schemas, validation, permissions, retries, and failure recovery.
• Build persistent sessions, agent memory, state management, delegation, and multi-agent workflows.
• Develop RAG systems using ingestion pipelines, embeddings, vector and hybrid search, reranking, and citations.
• Optimize prompts, context assembly, token efficiency, caching, model routing, latency, and inference costs.
• Build evaluations, tracing, monitoring, guardrails, and regression testing for agent behavior and tool execution.
• Integrate commercial and open-weight language models into reliable production services.

REQUIRED QUALIFICATIONS

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field, or equivalent practical experience.
• 5+ years of software engineering, machine learning, or AI engineering experience.
• Production experience building agent harnesses, agent runtimes, or complex LLM applications.
• Advanced Python skills, including asynchronous programming, APIs, testing, and production debugging.
• Strong Rust skills, with the ability to build, maintain, and contribute to production Rust services.
• Strong understanding of prompt engineering, context engineering, tool calling, MCP, and structured outputs.
• Experience with RAG, agent memory, embeddings, vector databases, and retrieval optimization.
• Experience with LangChain, LangGraph, LlamaIndex, PydanticAI, or comparable technologies.
• Experience evaluating and improving agent quality, reliability, latency, token usage, and cost.

STRONGLY PREFERRED

• Familiarity with PyTorch, TensorFlow, Hugging Face, ONNX, or vLLM.
• Fine-tuning experience using LoRA, QLoRA, PEFT, or comparable techniques.
• Knowledge of quantization, distillation, and efficient model inference.
• Understanding of mixture-of-experts architectures and model-routing systems.
• Knowledge of machine learning, deep learning, and natural language processing fundamentals.
• Experience with SQL, PostgreSQL/pgvector, Redis, data pipelines, cloud services, and Linux.
• Experience with coding agents, sandboxed execution, or durable workflow systems.
• Familiarity with TypeScript, Java, or Bash is an asset.

WHAT WE’RE LOOKING FOR

• You do not need experience with every framework or technology listed above.
• We are looking for someone who understands the underlying architecture of modern agentic systems.
• You should have personally built or made substantial contributions to meaningful production agent systems.
• You should be able to clearly explain your architectural choices, technical decisions, and trade-offs.

ABILITY TO COMMUTE / RELOCATE

• Vancouver, BC: Must reliably commute or plan to relocate before starting work.
• Work Location: In person.

Pay: $120,000.00-$180,000.00 per year

Work Location: In person