Senior AI Engineer
Summary
Architect and lead generative-AI systems (RAG, agentic workflows, LLM apps) using Python, vector search, and OCI services, while defining evaluation, guardrails, and safety at scale.
Job De ion Must Have
- 6-10 years of engineering experience, with recent depth in building generative-AI and LLM applications.
- Demonstrated track record architecting RAG, agentic, and LLM-powered systems in production.
- Experience defining evaluation, guardrails, and safety standards for LLM systems at scale.
- Proven ability to mentor AI engineers and review designs, prompts, and implementations.
- Strong interest in keeping pace with advances in generative AI.
- Experience with OCI Generative AI services and deploying generative AI on Oracle Cloud Infrastructure.
- Familiarity with fine-tuning, prompt optimization, and model customization.
- Experience in government or regulated environments with data residency and privacy constraints.
- Knowledge of evaluation tooling and LLM observability platforms.
- Experience integrating AI features into enterprise applications.
- Awareness of responsible AI and governance considerations.
- AI or cloud certifications.
- Architect generative-AI solutions, including retrieval augmented generation (RAG), agentic workflows, and LLM-powered applications.
- Lead model selection and evaluation strategy, balancing quality, cost, latency, and data residency requirements.
- Design and oversee evaluation frameworks, guardrails, and safety measures for AI systems.
- Define AI engineering standards and reusable patterns for prompt orchestration, embeddings, retrieval, and vector search.
- Design retrieval architectures, chunking and indexing strategies, and grounding approaches for RAG systems.
- Optimize generative-AI systems for cost, latency, and reliability at production scale.
- Integrate foundation models via APIs, including OCI Generative AI services, into client applications.
- Lead the design of agentic systems, including tool use, orchestration, and multi step reasoning flows.
- Mentor AI engineers and review their designs, prompts, and implementations.
- Partner with stakeholders and solution architects to shape AI roadmaps and scope use cases.
- Establish observability, evaluation pipelines, and quality metrics for deployed AI features.
- Stay current with the rapidly evolving generative AI landscape and assess new models, tools, and techniques.
- Bachelor's degree in Computer Science, Artificial Intelligence, or a related field; Master's preferred.
- Strong Python skills and experience with LLM application frameworks and orchestration (e.g., LangChain, LlamaIndex, or equivalents).
- Hands on experience with RAG, embeddings, vector databases, and retrieval design.
- Experience designing and building agentic systems and tool calling workflows.
- Experience defining evaluation, guardrails, and safety for LLM systems.
- Track record of architecting AI solutions and leading or mentoring engineers.
- Understanding of cost and latency optimization for foundation model applications.
- Ability to communicate technical designs and trade offs to technical and business stakeholders.