Internal AI Product Engineer
New
IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonGCPProduct ManagementSoftware ArchitectureGoDistributed Systems
Requirements
- Proven experience as a senior or staff-level back-end engineer with strong expertise in Go, Python, or similar programming languages.
- Hands-on experience building and operating AI/LLM-powered systems in production environments.
- Strong understanding of scalable cloud infrastructure and distributed systems, particularly on GCP or similar platforms.
- Product management mindset with experience owning initiatives from discovery and roadmap planning to measurable delivery outcomes.
- Experience designing APIs, integrations, and automation workflows for internal or enterprise systems.
- Strong knowledge of modern AI tooling, coding assistants, agent frameworks, plugins, and AI integration patterns.
- Ability to balance hands-on engineering work with strategic technical leadership and mentoring responsibilities.
- Excellent stakeholder management and communication skills, with the ability to align cross-functional teams around priorities and trade-offs.
- Strong analytical thinking, problem-solving abilities, and adaptability in fast-moving environments.
- Passion for AI innovation, automation, and building impactful internal developer and employee experiences.
Responsibilities
- Design, develop, and maintain scalable back-end services, APIs, and integrations supporting internal AI-powered tools and workflows.
- Architect AI-enabled systems that improve productivity, automation, and operational efficiency across teams.
- Evaluate technical approaches and trade-offs related to model selection, integrations, scalability, and build-versus-buy decisions.
- Lead discovery and product planning activities for internal AI initiatives, translating business needs into clear technical requirements and roadmaps.
- Build and maintain shared AI services, reusable tooling, and foundational AI capabilities for internal users.
- Collaborate with engineering, product, and business stakeholders to embed AI into cross-functional workflows and processes.
- Provide technical leadership through design reviews, mentorship, and guidance on AI engineering best practices.
- Support adoption and enablement of AI tools through demonstrations, integrations, and continuous improvements.
- Stay informed on emerging AI/ML technologies, frameworks, and tooling to identify new opportunities and optimize solutions.
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