Job Description Senior AI Engineer Agentic AI, LLM & Knowledge Graphs Position Summary We are seeking an experienced Senior AI Engineer to design, build, and operate production-grade AI systems that enable end-to-end customer experiences, increase straight-through processing, and optimize technology capabilities.

The ideal candidate will have hands-on experience delivering LLM and Generative AI solutions beyond the prototype stage , with robust software engineering and production operations expertise.

Required Skills & Experience 610 years of production software engineering experience, including hands-on delivery of AI/LLM systems .

Strong Java/JVM engineering experience; Kotlin or Scala preferred.

Strong software engineering practices including Git, code reviews, automated testing, structured logging, and clean design principles .

Hands-on experience with GenAI patterns including prompt engineering, structured/JSON outputs, tool/function calling, RAG, and agentic workflows .

Experience with Neo4j/Cypher and/or MongoDB Atlas .

Experience with vector search and embeddings for semantic retrieval.

Strong expertise in Agentic AI, Knowledge Graphs, GraphRAG, AI-enabled document generation, cloud infrastructure, CI/CD, and observability .

Experience with MCP (Model Context Protocol) and/or A2A (Agent-to-Agent) interfaces is highly desirable.

Key Responsibilities Design and build long-running, multi-stage agentic workflows that can pause, resume, and recover reliably.

Orchestrate LLMs and tools for retrieval, calculations, rules, and structured extraction.





Engineer prompts and structured-output contracts to produce validated, machine-readable results.

Build event-sourced workflows using frameworks such as Akka SDK , with persistent state, decisions, and evidence.

Design and maintain knowledge graphs containing entities, relationships, and source provenance.

Develop ingestion and extraction pipelines that transform source documents into validated, queryable graph structures.

Implement GraphRAG, vector retrieval, and embeddings to provide grounded AI responses.

Develop MCP tool servers and A2A interfaces and integrate with MCP-compatible clients and platforms such as Microsoft Copilot Studio.

Establish grounding, evaluation, and safety standards, including anti-hallucination controls, regression testing, edge-case testing, and human-in-the-loop reviews .

Implement guardrails for prompt injection, data minimization, and safe AI output generation .

Own the complete lifecycle from development through production deployment and operations .

Build and maintain CI/CD pipelines, environment configurations, secrets management, and access controls .

Work with enterprise AI services including managed model endpoints, search/retrieval services, document storage, OCR/document intelligence, and graph databases .

Implement logging, metrics, tracing, monitoring, and alerting for production AI systems.

Collaborate with engineering, business, and technology stakeholders to deliver secure, explainable, reliable, and business-ready AI solutions.

📌 Senior AI Engineer – Agentic AI, LLM & Knowledge Graphs (Toronto)
🏢 Astra North Infoteck
📍 Toronto