• Design and develop new AI-powered applications with browser-based and conversational interfaces to support modern HR functions. • Build and maintain shared infrastructure that supports a growing portfolio of agentic AI applications, including AWS EC2 servers, Airflow workflows, CI/CD pipelines, and Snowflake integrations. • Integrate LLM APIs into enterprise applications and HR workflows, delivering tangible AI-powered features. • Partner with HR stakeholders to translate needs into AI solutions that improve the employee experience. • Collaborate with data scientists to deploy and manage AI systems, ensuring scalability, reliability, and efficiency. • Experiment with and implement agentic frameworks to extend future AI capabilities.

• Design, build, and optimize real-time speech-to-text pipelines • Improve transcription accuracy through context injection • Develop and maintain LLM-powered post-processing • Build voice-to-action systems • Evaluate, benchmark, and integrate ASR models • Collaborate with product and platform teams

• Collaborate directly with the VP on prompt architecture, workflow design, and product roadmap. You’re a builder who shapes what gets built. • Own full-stack feature delivery from Postgres schema through API layer through React UI • Build and maintain multi-step AI pipelines: prompt chaining, structured output parsing, confidence scoring, failure recovery, and audit-trail logging • Integrate third-party financial data APIs into production tool workflows • Build financial document ingestion: parse uploaded spreadsheets and structured reports into typed data models for downstream AI processing • Maintain and extend the deterministic pre-processing and heuristic layers that make AI output reliable enough for audit • Contribute to the AI output evaluation framework: structured test inputs, expected outputs, scoring rubrics • Work cross-functionally with finance practitioners, product, design, and leadership to scope what gets built and push back on specs that miss

Role Description This is a remote role in the US and Canada. We are looking for a highly experienced Agentic AI Engineer with 7+ years of experience to design, build, and scale autonomous AI systems. This role focuses on developing advanced multi-agent systems capable of reasoning, planning, and executing complex workflows using LLMs. A key part of this role is implementing Spec-Driven Development (SDD), where structured specifications drive automated code generation, validation, and deployment workflows. You will lead the design of agent-driven platforms that automate SDLC, enterprise workflows, and decision systems. - Architect and build autonomous AI agents with advanced reasoning capabilities - Design multi-agent orchestration systems (planner, supervisor, executor) - Implement Spec-Driven Development (SDD) systems to convert requirements into executable workflows and code - Define and manage artifacts such as RequirementsPack, ArchitecturePack, and execution manifests - Design memory systems (vector DB, knowledge graph, hybrid RAG) - Optimize systems for scalability, latency, and cost - Integrate agents with enterprise platforms and APIs - Drive best practices in prompt engineering and context engineering - Mentor engineers and guide technical direction Qualifications - 7+ years of software engineering experience - 3+ years of experience with Generative AI / LLM systems - Strong programming skills in Python (preferred) or Go - Experience with distributed systems and backend architecture - Hands-on experience with cloud platforms (AWS preferred) - Proven experience designing scalable systems Requirements - LLM orchestration and reasoning systems - Prompt and context engineering - RAG and hybrid retrieval systems - Vector databases and semantic search - Agent frameworks (LangGraph, LangChain, or similar) - Multi-agent system design patterns - Spec-Driven Development (SDD) and spec-to-code workflows Preferred Qualifications - Experience building production-grade agent systems - Experience implementing SDD frameworks (OpenSpec, BMAD, or similar) - Familiarity with knowledge graphs and graph-based reasoning - Experience with Kubernetes, Docker, and scalable infrastructure - Experience with evaluation frameworks and guardrails Nice to Have - Experience with SDLC automation or coding agents - Familiarity with MCP or A2A communication patterns - Exposure to reinforcement learning or agent optimization - Experience in enterprise AI platforms What Success Looks Like - Deliver production-grade autonomous agents at scale - Successfully implement spec-to-code pipelines using SDD - Drive measurable impact through automation and AI - Improve system reliability, reasoning, and performance Benefits - Competitive Wages - Comprehensive Benefits package (medical, dental, vision, etc.) - Generous PTO to support work-life balance - 401K/RRSP Matching - Paid Parental Leave - Autonomy to grow and find your career path with supportive leadership - Remote working opportunities - Inclusive and diverse work environment