Artificial Intelligence Engineer

About the Role

This position serves as a critical bridge linking AI platform capabilities with their practical application within a technical, developer-driven environment. The incumbent will integrate closely with engineering teams to pinpoint barriers to AI platform adoption and usability, resolving these issues at the peer-technical level. This role focuses on facilitating platform integration and resolving adoption challenges rather than teaching or developing AI skills. Collaboration with the Team Lead will be key, acting as the main liaison between platform operations and engineering.

Key Responsibilities

• Embed with technical teams to perform comprehensive workflow assessments, identifying optimal AI tool placement, underuse areas, and operational or integration hurdles.
• Troubleshoot and resolve adoption issues related to platform integration, such as IDE plugin setup, API authentication, network/proxy configuration, SSO integration, and tool compatibility—working directly alongside developers.
• Maintain and update a catalog documenting AI tool compatibility with internal systems, pipelines, and developer environments.
• Analyze platform usage statistics by team to detect adoption lags, investigate their root causes, and coordinate targeted interventions with team leads.
• Assess new AI platform features upon release, evaluating their fit within existing workflows and advising on adoption decisions with technical evidence.
• Manage developer feedback concerning platform gaps and challenges, synthesizing input and communicating detailed findings to vendors.
• Coordinate with the Team Lead to ensure compliance with platform governance policies, including configurations, data handling, and access controls.
• Work with the Support Engineer to distinguish between systemic platform issues and user-specific errors, escalating and managing vendor interactions when necessary.

Required Qualifications

• Minimum of 4 years of hands-on experience in software, platform engineering, or developer tooling, with strong coding literacy to engage effectively with senior engineers.
• Proven direct experience in utilizing enterprise AI platforms within a professional software development setting, demonstrating integration of AI into engineering workflows.
• Expertise diagnosing issues across developer toolchains, including IDEs, CLI tools, API authentications, network configurations, CI/CD pipelines, and version control systems.
• Ability to work independently with seasoned technical professionals, evaluating workflows and delivering credible recommendations without supervision.
• Comfortable with analytics: proficient in acquiring platform telemetry, developing adoption dashboards, and applying metrics to inform operational decisions.

Mandatory Technical Skills

• Programming proficiency in Python, JavaScript/TypeScript, Go, Java, or Bash/PowerShell, capable of reading and writing code and replicating developer issues.
• Hands-on experience with at least one enterprise AI tool such as Anthropic Claude (Code or Cowork), GitHub Copilot, Cursor, Google Gemini for Workspace, or OpenAI ChatGPT Enterprise, including deployment, administration, or integration roles.
• Troubleshooting skills across multiple developer toolchain areas, including IDE extension deployment, CLI tools, REST APIs (with OAuth or token authentication), network proxies, and CI/CD systems like GitHub Actions or Jenkins.
• Practical knowledge of enterprise Single Sign-On technologies such as SAML or OIDC relevant to developer tool integration.
• Experience with SQL or similar query languages, alongside business intelligence tools like Looker, Tableau, Power BI, or Grafana for data reporting.
• Technical writing skills demonstrated by authoring documentation for engineering audiences using platforms like Confluence, Notion, or markdown-based systems.

Preferred Qualifications

• Familiarity with multiple enterprise AI platforms at a technical integration level, enabling platform comparisons, troubleshooting, and informed advising.
• Background in developer platforms, internal tooling, or developer experience functions within software product companies.
• Understanding of agentic AI operational patterns, including tool use, MCP servers, and complex workflows, with a focus on governance and operational risk management.
• Experience managing enterprise developer tooling ecosystems, including IDE plugin management, GitHub/GitLab integrations, and developer portal administration.

Eligibility

Open to applicants who have completed any graduate degree.