Senior AI Engineer

Below is a tailored cover‑letter (and a brief “quick‑facts” résumé snapshot) that you can copy‑paste, edit, and send to Procurify for the Senior AI Engineer – Gravenhurst role.
Feel free to adjust the personal details, specific project names, and metrics to match your exact experience.

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📄 Cover Letter – Senior AI Engineer (Procurify)

[Your Name]
[Your Address] • Gravenhurst, ON • [Phone] • [Email] • [LinkedIn] • [GitHub/Portfolio]

April 5 2026

Hiring Committee
Procurify
Remote‑First (Gravenhurst)

Dear Hiring Committee,

I am excited to apply for the Senior AI Engineer position at Procurify. With 7 + years of hands‑on AI/ML engineering, a proven track record of shipping production‑grade LLM‑powered features, and deep expertise in building scalable, cloud‑native microservices, I am confident I can help Procurify deliver the next generation of AI‑enhanced procurement solutions.

Why I’m a strong fit

Procurify requirement	My experience & impact
5+ years building AI features in production	Designed, implemented, and maintained a RAG‑based contract‑analysis service for a fintech SaaS (served > 200 k monthly active users) that reduced manual review time by 68 %.
LLM, prompt engineering, RAG, vector DBs	Daily work with OpenAI GPT‑4, Anthropic Claude, and Llama‑2; built LangChain‑driven multi‑agent workflows; deployed pgVector and Databricks Vector Search for semantic retrieval with sub‑50 ms latency.
Python + FastAPI/Flask/Django, microservices	Led a team of 4 engineers to refactor a monolith into FastAPI‑based microservices behind an API‑gateway, achieving 99.95 % uptime and 30 % cost reduction on AWS.
Cloud (AWS/GCP), Docker/K8s, CI/CD	Architected a Kubernetes‑native AI inference platform on EKS with Helm, ArgoCD, and GitHub Actions pipelines that auto‑scaled GPU nodes based on request volume.
Experimentation & A/B testing	Built an experiment framework (feature‑flag + metrics pipeline) that enabled weekly A/B tests of prompt variants, delivering a 12 % lift in answer relevance (measured by NDCG).
Observability & quality	Integrated OpenTelemetry, Prometheus, and Grafana for end‑to‑end latency tracing; instituted pytest‑based unit/integration suites with > 90 % coverage for all AI services.
Collaboration & communication	Regularly partnered with product, design, and data science teams; presented roadmap demos to C‑suite stakeholders and authored internal “AI‑Best‑Practices” documentation adopted company‑wide.

What I’ll bring to Procurify

1. End‑to‑end AI ownership – From data ingestion, vector indexing, and prompt design to model serving, monitoring, and continuous improvement.
2. Scalable architecture – A proven microservice pattern that isolates heavy‑weight LLM inference, enabling low‑latency, high‑throughput APIs that can be safely rolled out to millions of procurement transactions.
3. Innovation mindset – Hands‑on experience with agentic AI, tool‑use LLMs, and retrieval‑augmented generation that can be leveraged to automate invoice processing, spend‑analysis recommendations, and dynamic policy enforcement.
4. Culture of excellence – Commitment to clean code, rigorous testing, and knowledge sharing—aligned with Procurify’s “LEAD WITH CARES” values of Commitment, Ambition, Resilience, Excellence, and Simplicity.

I am particularly drawn to Procurify’s people‑first, remote‑first culture and its mission to help organizations spend smarter. The opportunity to shape AI‑driven procurement workflows while mentoring a growing engineering team feels like the perfect next step for my career.

Thank you for considering my application. I would love to discuss how my background and ideas can accelerate Procurify’s AI roadmap. I am available for a conversation at your convenience.

Sincerely,
[Your Name]

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📋 Quick‑Facts Resume Snapshot (optional attachment)

Name	Location	Phone / Email
[Your Name]	Gravenhurst, ON (remote)	(555) 123‑4567 • you@email.com

Professional Summary

Senior AI Engineer with 7 + years of experience delivering production‑grade LLM‑powered SaaS features. Expert in Python microservices, cloud‑native deployment, RAG pipelines, vector databases, and agentic AI frameworks. Proven leader who drives cross‑functional collaboration, builds high‑performing teams, and ships reliable, low‑latency AI systems at scale.

Core Competencies

• LLMs (GPT‑4, Claude, Llama‑2) • Prompt Engineering • Retrieval‑Augmented Generation (RAG)
• LangChain, Google AI‑SDK, Llama‑Index, Auto‑GPT frameworks
• Python (FastAPI, Flask, Django) • Microservice Architecture • Event‑driven design
• AWS (EKS, S3, SageMaker) • GCP (Vertex AI) • Docker • Kubernetes • Helm
• CI/CD (GitHub Actions, ArgoCD) • Terraform/IaC • Monitoring (Prometheus, Grafana, OpenTelemetry)
• A/B testing, hypothesis‑driven experimentation, metrics‑driven iteration
• Data pipelines (Airflow, Prefect) • ETL • Statistical analysis (pandas, scipy)

Selected Experience

Senior AI Engineer – FinTech SaaS (Remote)
Jan 2022 – Present

• Designed and launched a RAG‑based contract‑analysis microservice (FastAPI + pgVector) serving 200 k+ monthly users; cut manual review time by 68 %.
• Built LangChain multi‑agent workflow for automated expense‑policy compliance, reducing false‑positive alerts by 45 %.
• Architected Kubernetes inference platform on AWS EKS with auto‑scaling GPU nodes; achieved 99.95 % uptime and 30 % cost savings.
• Implemented A/B testing framework for prompt variants; drove 12 % lift in relevance scores (NDCG).
• Mentored a team of 5 engineers; instituted code‑review standards, testing coverage > 90 %, and internal AI‑best‑practices docs.

AI/ML Engineer – HealthTech Startup (Toronto, ON)
Jun 2019 – Dec 2021

• Developed clinical‑note summarization using GPT‑3.5 + RAG; deployed via Flask API with < 200 ms latency.
• Integrated vector search (Databricks) for semantic patient‑record retrieval, improving recall by 22 %.
• Set up CI/CD pipelines (GitHub Actions + Docker) and monitoring (Prometheus + Grafana) for all ML services.

Software Engineer – E‑Commerce Platform (Ottawa, ON)
Jul 2016 – May 2019

• Built high‑throughput REST APIs (Django + PostgreSQL) handling > 1 M daily transactions.
• Migrated monolith to microservices using Docker‑Compose, reducing deployment time from hours to minutes.

Education

• M.Sc. Computer Science (AI & ML) – University of Waterloo, 2016
• B.Sc. Computer Engineering – Carleton University, 2014

Certifications

• AWS Certified Solutions Architect – Associate (2023)
• LangChain Certified Engineer (2024)

Open‑Source Contributions

• LangChain‑Toolkit – Added vector‑store adapters for pgVector & Databricks (10 k+ stars).
• FastAPI‑Observability – Created middleware for OpenTelemetry tracing (maintained by 200+ developers).

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Next Steps

• Customize the cover letter with any specific project names or metrics you have.
• Attach the full résumé (the snapshot above can be expanded into a standard two‑page format).
• Send to the email listed in the job posting or apply through Procurify’s careers portal, referencing “Senior AI Engineer – Gravenhurst”.

Good luck! 🎉 If you’d like help polishing any part of the résumé, preparing for technical interview questions, or building a portfolio demo for the role, just let me know.