Software Analysis Engineering

Job Description - OCI Enterprise Engineering

IC4 Principal Developer - Enterprise AI Platforms Team

Oracle is seeking an experienced and driven AI Architect / Principal Developer to join the OCI Enterprise Engineering, Enterprise AI Platforms Team . This team builds, integrates, deploys, and supports enterprise-grade AI platforms used across Oracle, including employee-facing generative AI experiences, agentic AI capabilities, engineering automation platforms, and secure integrations with AI providers such as OpenAI, Anthropic, OCI Generative AI, Codex-style developer assistants, and related enterprise AI services.

OCI Enterprise Engineering provides modern enterprise services to Oracle’s internal businesses and is driving improved agility, performance, availability, and security across Oracle’s enterprise and development environments. We seek passionate, highly motivated, engineering-first individuals who can help deliver scalable AI capabilities with strong enterprise controls, with particular emphasis on Agent AI , AI-assisted software engineering , and Harness-based engineering workflows .

As an IC4 AI Architect, you will design and deliver platform modules, integrations, agent frameworks, developer productivity capabilities, and operational services that make AI usable, secure, measurable, and productive for Oracle employees and engineering teams. You will work across multiple delivery tracks, rapidly evaluate emerging AI capabilities, and turn practical ideas into reliable enterprise deployments that can be adopted safely at Oracle scale.

This role is especially focused on building the next generation of enterprise AI platforms: autonomous and semi-autonomous agents, AI-powered engineering assistants, Codex-like coding workflows, Harness engineering automation, secure tool execution, model orchestration, observability, governance, and production-ready deployment patterns.

Independently architect, design, and drive AI platform modules, provider integrations, APIs, agent runtimes, internal tools, and engineering automation services from concept through production release.

Agent AI platform development: Design and implement enterprise-grade Agent AI capabilities, including tool-calling agents, multi-step reasoning workflows, task orchestration, memory and context management, human-in-the-loop controls, agent evaluation, and safe execution patterns.

Build and integrate AI capabilities into Harness-based engineering workflows, including CI/CD automation, deployment intelligence, release assistance, pipeline troubleshooting, change analysis, incident support, and developer productivity enhancements.

Codex and AI-assisted engineering workflows: Evaluate, integrate, and operationalize Codex-style coding assistants and AI developer tools for Oracle engineering teams. Design secure workflows for code generation, code review assistance, test generation, documentation, refactoring, repository understanding, and engineering knowledge retrieval.

Enterprise AI deployment: Design secure, scalable deployment patterns for generative AI platforms and services such as OpenAI, Anthropic, OCI Generative AI, Codex-like engineering agents, and related enterprise AI capabilities.

Work effectively across parallel initiatives, balance priorities, identify dependencies, and make sound technical decisions with limited supervision.

Explore new AI features, model APIs, agentic workflows, RAG patterns, evaluation methods, engineering automation tools, and platform changes. Build prototypes that clarify enterprise value, risk, feasibility, and implementation approach.

Solution design and implementation: Translate business, employee productivity, and engineering productivity needs into well-structured AI solutions, including backend services, orchestration flows, prompt and tool integrations, model routing, repository integrations, pipeline integrations, and operational controls.

Design secure patterns for AI agents and coding assistants to interact with enterprise systems such as Git repositories, CI/CD platforms, Harness, Jira, Confluence, SharePoint, Outlook, observability tools, and internal APIs.

Embed enterprise security guardrails, identity and access controls, data protection practices, auditability, responsible AI controls, model risk management, prompt and code safety, and compliance requirements into platform architecture.

Design for reliability, observability, scalability, cost control, performance, supportability, incident response, and operational readiness across production AI services, agents, and engineering automation workflows.

Partner with product managers, security teams, platform engineers, application teams, developer experience teams, support teams, and business stakeholders to deliver AI capabilities that are practical, supportable, and aligned with Oracle standards.

Document design decisions, share learnings, mentor engineers, establish reusable patterns, and help the team stay current with fast-moving AI platform, agent, and AI-assisted engineering changes.

8+ years of experience in software engineering, cloud platforms, enterprise architecture, AI/ML engineering, developer platforms, DevOps engineering, or related technology roles.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or equivalent practical experience.
• Hands-on experience designing and building REST APIs, microservices, backend services, workflow orchestration, platform integrations, or developer productivity systems.
• Practical experience with generative AI, LLMs, prompt engineering, RAG, model APIs, embeddings, vector search, agent workflows, tool calling, or AI-assisted application development.
• Experience with developer engineering workflows such as CI/CD, build pipelines, deployment automation, release management, testing automation, code review, or production support.
• Strong understanding of secure enterprise deployment patterns, including authentication, authorization, network controls, secrets management, audit logging, data privacy, secure code handling, and least-privilege access.
• Ability to quickly learn new AI capabilities, assess tradeoffs, and recommend practical approaches for safe adoption within a large enterprise.
• Strong written and verbal communication skills, with the ability to explain complex AI, agent, platform, and engineering automation concepts to technical and non-technical stakeholders.
• Experience working with globally distributed teams and Agile delivery practice

Experience deploying employee-facing AI platforms, internal productivity tools, chat assistants, enterprise knowledge systems, engineering assistants, or agentic AI products.

Experience designing or integrating Agent AI systems that use tools, enterprise APIs, repository context, knowledge retrieval, workflow orchestration, or human approval flows.

Experience with Harness or comparable engineering platforms for CI/CD, deployment automation, feature delivery, release operations, governance, and developer workflows.

Experience with Codex-style AI coding tools, AI code generation, automated test generation, code review assistance, repository analysis, or AI-assisted software delivery.

Experience integrating multiple AI providers or designing abstraction layers for model routing, policy enforcement, observability, evaluation, fallback behavior, and cost controls.

Experience with content creation, document analysis, data analysis, deep research, enterprise search, software engineering workflows, or agent-based workflows in enterprise AI products.

Experience evaluating emerging AI capabilities and converting ambiguous requirements into working designs and production-ready delivery plans.

Experience defining evaluation frameworks for AI agents, coding assistants, retrieval quality, tool execution accuracy, safety, and enterprise readiness.

AI platforms and model APIs: OpenAI, Anthropic Claude, OCI Generative AI, Azure OpenAI, Codex-style coding agents, or similar enterprise AI services.

Agent AI and orchestration: Agent workflows, function/tool calling, multi-step task execution, planning, memory and context management, human-in-the-loop patterns, agent evaluation, guardrails, and secure tool execution.

LLM application patterns: AI-assisted software engineering: Codex-style coding assistants, code generation, test generation, code review support, repository understanding, refactoring assistance, documentation generation, and developer workflow automation.

Harness and DevOps engineering: Harness CI/CD, deployment pipelines, release automation, build systems, automated testing, Git workflows, deployment governance, observability integration, incident response, capacity planning, and cost optimization.

LangChain, LlamaIndex, Semantic Kernel, Hugging Face, PyTorch, TensorFlow, or similar AI development and orchestration frameworks.

OpenSearch, Elasticsearch, Oracle Database vector search, pgvector, Milvus, Pinecone, FAISS, embeddings, ranking, retrieval evaluation, and enterprise knowledge grounding.

Cloud and platform engineering: OCI, Kubernetes, Docker, Terraform, Helm, API Gateway, service mesh, object storage, IAM, Vault, networking fundamentals, and production platform operations.

Programming: Python, Java, TypeScript, or JavaScript; experience building production services, automation, agents, platform integrations, and developer tools is strongly preferred.

OAuth/OIDC, SSO, REST, event-driven integration, Slack, Confluence, SharePoint, Outlook, Jira, Git repositories, CI/CD systems, Harness, observability platforms, and comparable enterprise systems.

Responsible AI and governance: Secure prompt and data handling, model risk awareness, content safety, code safety, compliance controls, evaluation records, auditability, usage monitoring, and policy enforcement.

Independently architect, design, and drive AI platform modules, provider integrations, APIs, services, and internal tools from concept through production release.

Enterprise AI deployment: Design secure, scalable deployment patterns for generative AI platforms and services such as OpenAI, Anthropic, OCI Generative AI, and related enterprise AI capabilities.

Work effectively across parallel initiatives, balance priorities, identify dependencies, and make sound technical decisions with limited supervision.

Explore new AI features, model APIs, agentic workflows, RAG patterns, evaluation methods, and platform changes; build prototypes that clarify enterprise value, risk, and implementation approach.

Solution design and implementation: Translate business and employee productivity needs into well-structured AI solutions, including backend services, orchestration flows, prompt and tool integrations, model routing, and operational controls.

Embed enterprise security guardrails, identity and access controls, data protection practices, auditability, responsible AI controls, and compliance requirements into platform architecture.

Partner with product managers, security teams, platform engineers, application teams, support teams, and business stakeholders to deliver AI capabilities that are practical, supportable, and aligned with Oracle standards.

Design for reliability, observability, scalability, cost control, performance, and supportability across production AI services.

Document design decisions, share learnings, mentor engineers, and help the team stay current with fast-moving AI platform changes.

S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

May be eligible for bonus and equity.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.

Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following:

• Medical, dental, and vision insurance, including expert medical opinion
• Short term disability and long term disability
• Life insurance and AD&D
• Supplemental life insurance (Employee/Spouse/Child)
• Health care and dependent care Flexible Spending Accounts
• Pre-tax commuter and parking benefits
• Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. 11 paid holidays
• Employee Stock Purchase Plan
• Financial planning and group legal
• Voluntary benefits including auto, homeowner and pet insurance

The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.

Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives.

True innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs.

We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing View email address on jobs.institutedata.com is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.