- Company Name
- GitGuardian
- Job Title
- AI Engineer
- Job Description
-
**Job Title**
AI Engineer
**Role Summary**
Design, build, and maintain an internal AI platform that delivers business automations, agent‑based workflows, and data‑driven applications. Collaborate with data, analytics, and product teams to create scalable, user‑friendly tools that reduce manual effort and accelerate decision‑making across the organization.
**Expectations**
- Minimum 5 years in a technical or solutions role focused on production automations or tooling (Analytics Engineering, Solutions Engineering, Business Ops).
- Proven track record of deploying end‑to‑end automation solutions.
- Expert Python developer with experience building robust APIs, data pipelines, and lightweight applications.
- Hands‑on experience with generative AI, especially Dust, LangChain, RAG, and agentic workflows.
- Strong stakeholder management; able to translate business needs into scalable technical solutions.
- Comfortable using low‑code/visual tools (n8n, Zapier, Make) when appropriate, and Python for complex tasks.
- Product‑oriented mindset; design intuitive interfaces (CLI, web UI, chat) for non‑technical users.
**Key Responsibilities**
1. Design and implement business automations that connect systems (HubSpot, Notion, Linear, etc.) to eliminate manual workflows.
2. Build internal agents and wrap them in simple UIs/CLI/chat for self‑serve usage.
3. Partner with Analytics and Data Engineers to ingest, transform, and validate data from Snowflake, PostgreSQL, Elasticsearch, and external APIs.
4. Map high‑impact processes, propose scalable solutions, and champion adoption across teams.
5. Establish best practices, maintain tooling (Dust, n8n), and provide training documentation.
6. Own end‑to‑end lifecycle: discovery, development, deployment, monitoring, and iterative improvement.
7. Keep the platform current with emerging AI capabilities (retrieval‑augmented generation, evaluation, agentic workflows).
**Required Skills**
- Advanced Python programming (APIs, data manipulation, scripting).
- Knowledge of n8n (or similar low‑code workflow systems).
- Experience with Dust, LangChain, and generative‑AI concepts (RAG, prompts).
- Strong SQL skills and familiarity with Snowflake data warehousing.
- Ability to prototype lightweight UIs/CLI or chat interfaces.
- Excellent communication and stakeholder engagement.
- Understanding of CI/CD, containerization (Docker), and orchestration (Kubernetes).
**Required Education & Certifications**
- Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Data Science, or related field.
- Optional certifications: AI/ML, cloud (e.g., AWS, GCP), or data engineering relevant to the stack.