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Oci Data Jobs

2 jobs found

1d ago

Lead Principal Machine Learning Engineer

Oracle Seattle, WA

Seattle, WA

1d ago

Full time Ai Ml Ai Platform Artificial Intelligence

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Job Description

Oracle is seeking a Lead Principal Machine Learning Engineer to define, build, and operate production-grade agentic AI platforms on Oracle Cloud Infrastructure. The role provides technical leadership and architectural direction across distributed AI systems to ensure reliable, secure, and cost-efficient production services. The position is based onsite in Seattle, Washington.

Responsibilities

Assume senior technical ownership for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Lead architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, converting broad goals into executable multi-quarter plans and milestones.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
Mentor staff and senior engineers, raise architectural standards, and influence engineering practices across OCI without requiring direct management authority.
Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.

Requirements

Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience.
12+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating Senior Staff or Principal-level impact.
Proven track record as a Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
Strong programming skills in Python and ability to contribute high-quality production code, reviews, tests, and debugging in complex distributed environments.
Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
Strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
Excellent written and verbal communication, with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Technologies

Oracle Cloud Infrastructure (OCI)
Python
Kubernetes
Docker
LangGraph
LangChain
CrewAI
AutoGen
LlamaIndex
Model Context Protocol (MCP)
Codex
Claude Code
Cursor
Copilot

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6d ago

Principal Data Engineer

Oracle Nashville, TN

Nashville, TN

6d ago

Full time Senior Analytics Big Data

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Job Description

The Principal Data Engineer role based in Nashville, Tennessee (onsite) leads Data Engineering, BI, and Analytics initiatives for OCI, blending hands-on engineering with program leadership to design scalable data platforms and reporting solutions across Oracle Cloud Infrastructure.

Responsibilities

Design, build, and scale data pipelines that consolidate data from multiple OCI systems and services.
Create robust data models, datasets, and reporting frameworks supporting engineering, operations, customer success, and executive leadership.
Architect scalable analytics platforms that undergird strategic customer programs and operational decisions.
Develop enterprise-grade data solutions to improve visibility into customer adoption, health, service performance, and business outcomes.
Automate data ingestion, transformation, and reporting processes to reduce manual effort and increase data accuracy.
Establish standards for data quality, governance, lineage, and observability across critical datasets.
Collaborate with engineering teams to define telemetry, instrumentation, and data collection strategies.
Perform in-depth analyses of large, complex datasets to surface trends, opportunities, risks, and bottlenecks.
Promote modern data engineering practices, tools, and technologies across the organization.
Lead large, cross-functional initiatives spanning engineering, product, operations, and executive leadership.
Decompose ambiguous business problems into actionable technical workstreams and measurable deliverables.
Develop functional specifications and drive execution from concept through delivery.
Identify process gaps and implement scalable mechanisms to improve efficiency and execution.
Manage program schedules, dependencies, risks, and stakeholder communications.
Anticipate bottlenecks, escalate when needed, and balance technical constraints with business priorities.
Align OCI organizations toward shared objectives and customer outcomes.
Engage with cross-functional teams including Engineers, Product Managers, Architects, Customer Success leaders, and Executive Leadership.
Operate effectively in a fast-paced, ambiguous environment while delivering measurable business value.

Data Engineering & Analytics Leadership

Mentor junior team members to capture data requirements and business objectives for initiatives.
Contribute expertise to the design and construction of data infrastructure that optimizes processing from diverse sources.
Analyze, design, and troubleshoot data flows, participating in architecture reviews for performance and security.
Adapt data collection processes and ETL pipelines for better efficiency and accuracy.
Engage with upstream and downstream teams to ensure adherence to defined SLAs.
Manage relationships with data providers to sustain reliable data access.

Business Intelligence & Executive Reporting

Deliver BI solutions that provide clear visibility into customer health, operations, and strategic objectives.
Develop executive dashboards, KPI frameworks, scorecards, and reporting used by senior leadership.
Partner with business leaders to define success metrics and reporting requirements.
Build scalable semantic models and datasets enabling self-service analytics across units.
Transform raw data into actionable insights and recommendations for decision makers.
Standardize reporting methodologies and establish trusted sources of truth for key metrics.
Support strategic planning, investments, and customer engagement through data-driven analysis.

Technical Program Management & Strategic Execution

Lead large, cross-functional programs spanning engineering, product, operations, and leadership.
Break down complex problems into executable technical workstreams with clear deliverables.
Draft functional specifications and drive end-to-end delivery from concept to rollout.
Identify process gaps and implement scalable mechanisms to improve organizational efficiency.
Oversee program schedules, dependencies, risks, and stakeholder communications.
Manage bottlenecks, escalations, and balance technical constraints with business priorities.
Coordinate across OCI teams to pursue shared objectives and customer outcomes.
Lead collaborations with Engineers, Product Managers, Architects, Customer Success leaders, and Executives.
Operate effectively in a fast-moving, ambiguous environment while delivering value.

Data Processing & Pipelining — Data Requirements, Collection, and Infrastructure

Mentor team members to identify data requirements and business objectives for initiatives.
Provide expertise in designing and building data infrastructure to optimize processing from diverse sources.
Independently analyze, design, and troubleshoot data flows aligned with business needs.
Participate in architecture, performance, and security reviews of technical solutions.
Refine data collection processes for indexing and query performance.
Develop ETL pipelines to support scalable data collection and extraction.
Ensure upstream and downstream teams comply with defined SLAs and data contracts.
Manage relationships with data providers to sustain reliable data access.

Data Processing & Pipelining — Data Governance

Design and implement data governance policies to ensure data consistency, integrity, and reliability across the lifecycle.
Lead redaction of PII and PHI data to maintain privacy and security compliance.
Minimize data collection and usage in line with data minimization principles.
Implement data security measures to prevent unauthorized access or misuse, and escalate issues as needed.
Ensure data handling complies with applicable laws, regulations, and standards.

Data Processing & Pipelining — Data Validation & Quality Assurance

Contribute to data validation and integrity checks to prevent quality issues in pipelines and models.
Mentor on data annotation and labeling to uphold data quality standards.
Identify opportunities to automate validation and governance workflows.
Correct deviations and non-conformances independently when identified.

Data Pipeline & Solutions Engineering — Pipeline Design

Apply advanced ETL knowledge to design and optimize automated, scalable data pipelines and reusable data products.
Implement storage solutions enabling efficient access and analysis of processed data.
Mentor team members to manage data flow and storage operations.

Data Pipeline & Solutions Engineering — Data Solutions Engineering

Work autonomously and with peers in an agile environment to build scalable, cost-effective data solutions.
Review code, assist with testing and debugging, and evaluate new technologies for robust data solutions.
Enforce coding standards and document design decisions for architecture alignment.
Document data-driven design choices and secure necessary approvals with evidence.

Core Responsibilities — Planning & Execution

Oversee moderately complex tasks, ensuring timely delivery and requirement adherence for projects.
Delegate, monitor, and prioritize work across multiple initiatives, adjusting plans as resources shift.

Core Responsibilities — Collaboration & Partnership

Collaborate across the organization to align expectations and achieve shared goals.
Leverage relationships with business leaders, stakeholders, and customers to ensure solutions meet needs.
Promote inclusive practices by listening to diverse perspectives and ensuring each voice is heard.

Core Responsibilities — Problem Solving

Address moderately complex issues by analyzing data to derive solutions consistent with standard practices.
Escalate unresolved issues with thorough assessment and propose potential remedies.
Document problem-solving approaches and continuously improve strategies.

Core Responsibilities — Continuous Learning

Pursue opportunities to expand knowledge, staying current with industry trends and tools.
Seek feedback and training to enhance skills, and mentor junior colleagues.

Core Responsibilities — Continuous Improvement

Propose and implement process improvements to increase efficiency and effectiveness across teams.
Solicit feedback on new approaches and methods to support ongoing advancement.

Core Responsibilities — Performance & Development

Contribute to talent development by participating in candidate evaluations and providing hiring input.