Description review
Senior Generative AI Engineer
Inizio Partners Corp · Canada · back to the listing
HR standards
55/100
needs work
Title ↔ description
89/100
strong
Reads as
Machine Learning Engineer
90% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
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What the listing never says
- 22 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Senior Generative AI Engineer
Background
We are looking for a Senior Generative AI Engineer to design, build, and ship production-grade Generative AI and Agentic AI applications that delivery business value across the organization. This role is focused on building AI applications and services at scale. You will be responsible for building robust, secure, and highly scalable systems that integrate with leading cloud-based AI services.
You will work alongside product managers, designers, and other engineers as an individual contributor. You are expected to own features end-to-end, and to deliver high-quality, reusable code that scales beyond a single use case.
Key Responsibilities
Software Engineering and Execution
• Design, build, and ship production-grade Generative and Agentic AI features and applications
• Own features end-to-end from technical design through implementation, testing, deployment and operation
• Build reusable, well-abstracted components and shared utilities (e.g., RAG building blocks, agent scaffolding, evaluation harnesses, prompt utilities) to enable faster delivery of future Generative and Agentic AI products
• Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
• Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
• Build Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
• Build clean, well-tested RESTful and/or gRPC APIs with a focus on reliability, security, and performance
• Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
• Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
• Participate actively in code reviews and design discussions, sharing knowledge with peers
Required Qualifications
• 5-7 years of professional software engineering experience with at least 3 years of experience building AI/ML software products
• Bachelor's degree in Computer Science or a related field (Master's degree preferred)
• Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
• Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
• Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
• Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
• Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
• Solid understanding of API design, distributed systems, and cloud-native architecture
• Track record of taking systems from design through production deployment and operation
Preferred Qualifications
• Experience with containerization and orchestration (Docker, Kubernetes)
• Knowledge of Generative AI Risk Management frameworks (NIST RFM)
• Experience supporting developer platforms or internal tooling
Originally posted on Himalayas
Background
We are looking for a Senior Generative AI Engineer to design, build, and ship production-grade Generative AI and Agentic AI applications that delivery business value across the organization. This role is focused on building AI applications and services at scale. You will be responsible for building robust, secure, and highly scalable systems that integrate with leading cloud-based AI services.
You will work alongside product managers, designers, and other engineers as an individual contributor. You are expected to own features end-to-end, and to deliver high-quality, reusable code that scales beyond a single use case.
Key Responsibilities
Software Engineering and Execution
• Design, build, and ship production-grade Generative and Agentic AI features and applications
• Own features end-to-end from technical design through implementation, testing, deployment and operation
• Build reusable, well-abstracted components and shared utilities (e.g., RAG building blocks, agent scaffolding, evaluation harnesses, prompt utilities) to enable faster delivery of future Generative and Agentic AI products
• Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
• Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
• Build Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
• Build clean, well-tested RESTful and/or gRPC APIs with a focus on reliability, security, and performance
• Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
• Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
• Participate actively in code reviews and design discussions, sharing knowledge with peers
Required Qualifications
• 5-7 years of professional software engineering experience with at least 3 years of experience building AI/ML software products
• Bachelor's degree in Computer Science or a related field (Master's degree preferred)
• Strong proficiency in Python, with deep software engineering fundamentals (abstraction, modularity, system design, testing, performance)
• Hands-on experience building and shipping Generative and Agentic AI applications, including LLM integration, prompt engineering, and/or agentic workflows
• Practical experience integrating cloud-hosted LLM APIs such as Azure OpenAI, Vertex AI, and/or AWS Bedrock
• Experience with agent frameworks (e.g., LangChain, LangGraph, Google ADK, Claude Agent SDK) and vector databases (e.g., Pinecone, Weaviate, pgvector, Open Search, AlloyDB)
• Hands-on experience with Google Cloud Platform (GCP), Amazon Web Services (AWS), or Azure
• Solid understanding of API design, distributed systems, and cloud-native architecture
• Track record of taking systems from design through production deployment and operation
Preferred Qualifications
• Experience with containerization and orchestration (Docker, Kubernetes)
• Knowledge of Generative AI Risk Management frameworks (NIST RFM)
• Experience supporting developer platforms or internal tooling
Originally posted on Himalayas