Oracle AI & OCI Engineer / Developer

Salary: $113,000 - 153,000 per year Requirements:

• 8+ years of hands-on experience in software, data, cloud, platform, or database engineering, including recent delivery of AI/ML or GenAI applications.
• Strong Python and REST API development skills, with solid SQL/PLSQL and Oracle Database experience.
• Practical experience with LLM applications, RAG, embeddings, vector search, prompt engineering, agent and tool orchestration, and AI evaluation.
• Hands-on data engineering experience with ETL/ELT, document processing, metadata, data quality, APIs, structured and unstructured data, and retrieval pipelines.
• Hands-on OCI experience across IAM, networking, security, databases, logging and monitoring, automation, and cloud-native deployment.
• Practical experience with Terraform, Git, CI/CD, Linux, containers, secrets management, observability, and troubleshooting.
• Working knowledge of AI and application security, threat modeling, API security, authorization, encryption, logging/SIEM, and LLM-specific security risks.
• Ability to independently take work from requirements and architecture through working code, deployment, testing, demonstration, and production-transition materials.
• Bachelors degree in Computer Science, Engineering, Data Science, Artificial Intelligence, Information Systems, Cybersecurity, or a related field; a masters degree is preferred for lead-level roles.
• Preferred: OCI Generative AI or AI Foundations certification, and OCI DevOps or Architect certification.
• Preferred: Oracle Database certification or experience with Autonomous Database or OCI Data Integration.
• Preferred: OCI Security experience; CISSP, CCSP, or an equivalent security certification is advantageous.
• Preferred: Kubernetes/OKE, workflow or agent frameworks, FinOps/cost optimization, or cloud observability experience.
• Preferred: Delivery experience in U.S. Federal, state/local, DoD, healthcare, financial, or other regulated-data environments.
• Preferred: Knowledge of NIST/FedRAMP controls, DoD RMF/DISA Impact Levels, government data handling, governance, and lineage practices.
• For applicable public-sector engagements, candidates should be able to meet the customers relevant security, data-handling, citizenship, background-investigation, and clearance requirements. An active clearance is preferred where relevant, but is not required for every Innovation Lab assignment.

• Lead hands-on development of secure GenAI, RAG, and agentic AI applications using OCI Generative AI, approved models, enterprise data, APIs, tools, and workflows.
• Build Python services, REST APIs, prompts, tool integrations, guardrails, evaluation logic, error handling, and demonstration interfaces.
• Create RAG pipelines for document ingestion, chunking, enrichment, embeddings, vector indexing and search, metadata filtering, reranking, grounding, and source citations.
• Design and implement governed AI agents with identity and authorization controls, approved tool access, workflow orchestration, and human approvals where required.
• Configure and optimize Oracle Database and Oracle AI Database for vector storage and indexing, similarity search, metadata, retrieval, SQL/PLSQL processing, and RAG or agent workloads.
• Develop structured and unstructured ETL/ELT and ingestion pipelines connecting Oracle databases, enterprise applications, files, APIs, and approved external data sources.
• Apply data quality, lineage, masking, retention, access control, environment separation, and synthetic or de-identified data practices for PoVs.
• Provision and maintain OCI environments using infrastructure as code; create reusable Terraform modules and standardized development and deployment approaches.
• Build CI/CD pipelines for AI applications, APIs, data pipelines, infrastructure, and configuration, managing Git, artifacts, versions, secrets, promotion, and rollback.
• Implement container and, where appropriate, Kubernetes/OKE deployment patterns, along with secure networking, IAM, connectivity, logging, metrics, tracing, observability, and cost monitoring.
• Embed security by design, including IAM and authorization, encryption, secrets, API security, audit logging, threat modeling, vulnerability testing, and secure SDLC practices.
• Test LLM-specific risks such as prompt injection, data leakage, hallucinations, unsafe tool use, authorization bypass, groundedness, refusal behavior, and citation traceability.
• Instrument applications to track latency, retrieval quality, model and token usage, errors, task completion, security events, and operational KPIs.
• Troubleshoot and optimize performance across applications, model integrations, database and vector retrieval, data pipelines, OCI platforms, and deployments.
• Package reusable accelerators, source-code templates, IaC modules, ingestion components, evaluation suites, test data, deployment automation, and operational runbooks.
• Lead code and design reviews and mentor engineers while remaining directly accountable for working code and demonstrable technical results.
• Take PoVs through agency demonstrations and technical hardening toward pilot- or production-ready implementations, including deployment, security remediation, documentation, and operational handoff.
• Deliver secure RAG and agentic AI accelerators, agency-specific PoVs and applications, AI-ready ingestion pipelines, Oracle vector/RAG data layers, OCI environments, automated deployment patterns, security tests, dashboards, documentation, and operations materials.
• Track and improve PoV delivery and transition rates, retrieval quality, agent task completion, pipeline reliability, data quality, deployment success, security control coverage, auditability, availability, performance, cost visibility, recovery time, automation, and component reuse.

• Agentic AI
• AI
• AI Agents
• API
• Architect
• CI/CD
• Cloud
• DevOps
• ETL
• Git
• IAM
• Support
• Kubernetes
• LLM
• Linux
• Oracle
• Python
• RAG
• REST
• SQL
• Security
• Terraform
• DevSecOps

More:

We are ExpediteInfoTech (EIT), an equal opportunity employer. This hands-on engineering lead will work across the EIT OracleAI Innovation Lab, guiding solutions from agency requirements and discovery through design, build, Proof-of-Value, security and governance validation, demonstration, production hardening, and potential pilot or production opportunities. The role may support U.S. Federal, state/local, or DoD engagements, with applicable customer requirements varying by assignment.

last updated 42 week of 2026