Senior AI Developer

• Does this position require a security clearance? No
• Years 3 to 5+ years
• Additional Info Visa / work permit sponsorship is not available for this position
• Applicants are required to read, write, and speak the following languages English

We’re looking for an AI Developer to help shape the future of AI  ideal candidate has a strong foundation in data science and applied machine learning, with practical exposure to building agentic workflows (e.g., RAG, NL-to-SQL, microservices). You will collaborate with product, engineering, data, and security teams to deliver reliable, compliant, and scalable AI capabilities. You take ownership of features and services, make thoughtful trade-offs, and contribute to engineering excellence.

What You’ll Do:

Build AI-Powered Applications

• Design and implement features in AI-driven applications, primarily using Python or similar languages.
• Partner with cross-functional teams to deliver reliable, scalable solutions.

Data, Experimentation, and Evaluation

• Execute data preparation (feature selection, ETL, data quality) and contribute to robust evaluation frameworks.
• Run experiments, analyze results using appropriate metrics, and iterate to improve performance and reliability.

MLOps and LLMs

• Contribute to model deployment, monitoring, versioning, and guardrails for safety and reliability.
• Design and implement agentic workflows using frameworks like Lang Graph (or similar), including grounding with RAG and tool use.

Responsible AI and Compliance

• Apply privacy-by-design and secure coding practices; partner with security and compliance teams as needed.

Oracle Fusion and Conversational UX

• Integrate AI features into Oracle business applications.
• Contribute to intuitive, user-centric conversational interfaces.

Qualifications required:

• Degree (or equivalent experience) in Computer Science, Engineering, Mathematics, Physics, Statistics, or related field.
• Proficiency with at least one programming language—Python preferred.
• Hands‑on experience with ML libraries (e.g., Scikit‑learn, Tensor Flow, PyTorch).
• Experience with cloud platforms, ideally OCI (also valued: AWS, GCP, Azure).
• Understanding of software engineering fundamentals, data structures, algorithms, and secure SDLC practices.
• Strong communication skills; effective collaboration across product, engineering, and security/compliance stakeholders.
• Demonstrated contribution to production ML/LLM systems (e.g., services, pipelines, or features in production).

Optional Architecture & Design Skills (Preferred):

• Working knowledge of software architecture fundamentals and system design patterns (e.g., microservices).
• Practical experience modeling with UML and/or the C4 model; ability to produce sequence, class, and deployment diagrams that stay in sync with code.
• Familiarity with DDD techniques: identifying bounded contexts, strategic design, event storming, aggregate design, and context mapping.
• API and integration design: RESTful standards, gRPC, Graph
  
  QL, API gateways, schema versioning, and backward compatibility strategies.
• Event-driven architecture: experience with messaging systems (e.g., Kafka) and reliable event processing basics (ordering, retries, idempotency).
• Data and storage design: relational vs. No
  
  SQL trade-offs, indexing, caching strategies, and clear data contracts.
• Data governance: handling sensitive data with appropriate classification, retention, lineage, consent, and access controls aligned to privacy/compliance policies.
• Observability: designing for metrics, logging, tracing; SLOs, error budgets, and performance profiling.
• Security‑by‑design: basic threat modeling, secure defaults, secrets management, dependency scanning, and secure SDLC practices.
• Architecture documentation tools familiarity (e.g., Plant
  
  UML, Mermaid, draw.io).
• Exposure to cloud‑native architecture on OCI (preferred) or AWS/GCP/Azure: networking, IAM, container orchestration, service meshes, and managed AI/ML services.

Optional Nice to Have:

• Led or contributed to architecture spikes/prototypes and translated findings into solution patterns or reference implementations.
• Participation in design reviews or architecture forums; ability to articulate trade‑offs to…